Domain libraries · entity catalog

iris library

Authored subsystem deep-dive for iris, layered on the code-linked entity catalog — what each system is, why it exists, and how it fits.

authored deep-dive
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The libs/iris/ area: ~262 Nx libraries that make up Iris, Oshun's AI-assistant domain — the conversation engine, agent runtime, knowledge/RAG, four-tier memory, multimodal (voice/vision/BCI/spatial) I/O, emotional intelligence, personalization, privacy/safety, platform tooling, and multi-language SDKs.

What this area is#

Iris is the platform's conversational and agentic AI substrate, and by project count it is the largest single lib area in the monorepo. It is not one package but 262 separate Nx libraries under libs/iris/, each scoped scope:iris (18 tagged scope:shared and 1 tagged scope:oshun) and almost all implemented in TypeScript. The packages are organised by capability sub-system rather than as one monolith, so a consumer can pull in only the slice it needs — e.g. just @iris/conversation-core and one provider, or the full agent + tools + computer-use stack.

The area layers roughly like this. A foundation tier (@iris/core, @iris/types, @iris/config, @iris/embeddings) owns shared types, errors, context, configuration, and the canonical embedding client. A conversation tier owns multi-turn dialogue (@iris/conversation-core), intent/context/state/style/uncertainty modules, the provider-agnostic orchestrator (@iris/conversation-orchestration), and concrete provider adapters for Anthropic, OpenAI, Google, and local Ollama models. An agents tier (libs/iris/agents/) owns the runtime (@iris/agents-core), archetypes, multi-agent orchestration, a tool framework, and a full computer-use/desktop-automation stack (including a real multi-crate Rust native backend). A knowledge tier (libs/iris/knowledge/) is a production-grade RAG/GraphRAG/retrieval/grounding stack, and a memory tier (libs/iris/memory/) implements a four-tier memory hierarchy plus personalization and privacy sub-trees. Further tiers cover multimodal (vision, voice, BCI, spatial/XR, IoT), emotional intelligence, privacy/safety/security, accessibility, platform (gateway, billing, rate-limiting, SDK codegen, white-label), presence, analytics, integrations with six sibling Oshun domains, testing, and client SDKs in five languages.

Honesty note on maturity: the overwhelming majority of these libraries contain real, domain-specific logic (scoring formulas, retrieval fusion, state machines, crypto primitives, audio/turn-taking heuristics, statistical tests) and concrete exported classes/factories — they are not empty scaffolds. Many use injectable dependency seams and in-memory stores so the algorithms run without external infrastructure, with real backends (Postgres/Qdrant/Redis, vendor LLM/STT/TTS APIs) wired behind provider interfaces. A small set of nodes are deliberately thin V1 product-surface facades — a single index.ts exporting product metadata, descriptors, and validators (@iris/accessibility, @iris/agents, @iris/conversation, @iris/multimodal/vision, @iris/multimodal/voice). Those are called out as such in their entries below rather than overclaimed.

How it fits the wider system#

These libraries are consumed by the Iris product surfaces (web shell, mobile/desktop companions, the BFF, and the agent loop) and by sibling Oshun domains through the libs/iris/integrations/* adapters (Hathor, Maya, Nyx, Psyche, Sophia, Yemaya). The wire contracts for the domain live separately in @iris/contracts (libs/contracts/iris), which is the bottom-of-graph schema package the contracts area documents; the libraries here are the implementation behind those contracts. Provider adapters compose with the orchestrator; tools and computer-use compose with the agent runtime; knowledge/RAG and memory compose into the conversation pipeline; privacy/safety/accessibility wrap every surface. The five SDKs (@iris/sdk and the Kotlin/Python/Rust/Swift siblings) are the external client view of the same API. Walk the dependency edges on any node below to see exactly who composes with it.

Entity catalog (262)#

The 262 tracked Nx projects in iris, each a code-linked entity node — package, type, source path, declared targets, and its internal dependency graph (depends-on / used-by, resolved from the package manifests, §6/§8), read from the project graph. Grouped by architectural layer; walk the dependency links to travel the system. 262 of these carry an authored deep-dive (what / why / how it fits); the rest are generated scaffolds awaiting one.

agent (2)#

lib

@iris/computer-use-native

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Rust native backend (libs/iris/agents/computer-use/native). A multi-crate workspace (iris-desktop-core traits + per-OS crates for X11/Wayland/macOS-CGEvent/Windows-SendInput

  • an iris-desktop-napi napi-rs cdylib). X11 has real input/capture and a Task 6.4 native fixture; macOS and Windows have input/capture bodies; Wayland and every native accessibility-tree walker remain incomplete. The README records the per-backend boundary and #[cfg(target_os)] selection.
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@oshun/iris-computer-use-native

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TypeScript wrapper around the iris/computer-use Rust desktop binding (V1-P2-0093).

TypeScript wrapper (libs/iris/agents/computer-use/native/ts) around the Rust desktop binding — OshunDesktopController exposes capture, mouse, keyboard, clipboard, display, and capability methods, while unsupported backend methods fail closed. DesktopError mirrors the native error categories. Task 6.4 proved the wrapper plus X11 capture/input path on an isolated GTK/Xvfb target; native X11 clipboard remains unsupported.

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agents (1)#

lib

@iris/screenshot-vision

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Screenshot understanding and visual UI analysis for AI agents

Screenshot understanding for agents: ScreenAnalyzer, UIElementDetector, TextExtractor, LayoutAnalyzer, ChangeDetector, wrapped by ScreenshotVisionAgent.

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contracts (2)#

lib

@iris/types

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Iris AI Assistant shared type definitions

Shared Iris type definitions: conversation/memory/agent/model/user/tool/event types — a contracts-layer (layer:contracts) package consumed across the area.

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core (1)#

lib

@iris/core

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Iris AI Assistant foundation library - configuration, context, errors, logging, and core utilities

Foundation library: shared types, error codes/base, context + correlation/tracer/profiler, a logger, decorators, schemas, and a config loader (~26 modules) — the bottom of the Iris dependency graph.

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data (1)#

lib

@iris/memory-persistence

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Iris AI memory persistence layer - PostgreSQL, Qdrant, and Redis backends with backup/restore

Durable persistence backends: PostgresStore, QdrantStore (vector), RedisCache, plus backup/restore/recovery (with an S3 backup client), composed as a MemoryPersistenceSystem (constructable from env). The real-infrastructure layer behind the memory tier.

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domain (67)#

accessibility-* (8)#

lib

@iris/accessibility-cognitive

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Cognitive accessibility support for Iris - simplified language, step-by-step guidance, and memory aids

Cognitive-accessibility services for users with cognitive disabilities — reading assistance/pace, simplified language, memory aids, distraction reduction, step-by-step guidance, text highlighting — with named presets (PRESET_ADHD, PRESET_READING_SUPPORT, …) and an applyPreset composer. Substantial (~14 modules).

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@iris/accessibility-hearing

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Hearing accessibility support for Iris - visual alerts, captioning, and vibration feedback

Hearing-accessibility support for deaf/HoH users: visual alerts, vibration feedback, real-time captioning, transcript generation, and a sign-language avatar, composed by createHearingAccessibilityServices.

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@iris/accessibility-i18n

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Internationalization support for Iris - multi-language, RTL layouts, cultural adaptation, and localized formatting

Internationalization layer (~16 modules) — language support, RTL layout, cultural adaptation, localized date/number formats, translation memory, real-time/UI/content translation — with ~11 locale presets (I18N_PRESET_AR_SA, _JA, _ZH_CN, …).

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@iris/accessibility-motor

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Motor accessibility and voice-only operation support for Iris

Motor-accessibility / voice-only operation: voice recognition, voice commands/navigation, dictation, switch access, eye tracking, predictive and custom input, via createMotorAccessibilityServices.

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@iris/accessibility-visual

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Visual accessibility and screen reader support for Iris

Visual accessibility / screen-reader support: ScreenReaderOptimization, ARIALabels, FocusManagement, KeyboardNavigation, AnnouncementSystem, via createVisualAccessibility.

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@iris/accessibility-visual-alternatives

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Visual alternatives including high contrast, audio descriptions, and spatial audio for Iris

Visual alternatives — HighContrastModes, AudioDescriptions, TextAlternatives, SpatialAudioNavigation — composed by the VisualAlternatives class.

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@iris/accessibility-visual-display

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Adjustable display settings including text sizing, color contrast, font choices, and reduced motion for Iris

Adjustable-display controls: TextSizing, ColorContrast, FontChoices, ReducedMotion, composed by createAdjustableDisplay.

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code-* (6)#

lib

@iris/code-agentic

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Agentic coding capabilities with multi-file operations, refactoring, bug fixing, and feature implementation

Agentic coding: AgenticCoder, MultiFileChanger, RefactoringEngine, BugFixer, FeatureImplementer for multi-file code operations.

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@iris/code-generation

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Comprehensive code generation library with builders, generators, test generation, documentation generation, and contextual autocomplete

Code generation: a TypeScript AST generator with fluent builders (expression/statement/ function/class), test-generator, doc-generator, and contextual autocomplete.

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@iris/code-reasoning

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Code reasoning and analysis library for Iris conversation engine

Code reasoning (libs/iris/conversation/reasoning/code): AST/static analysis, a RuntimeBehaviorPredictor, and a BugHypothesisGenerator, composed as CodeReasoner.

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@iris/code-semantic

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Semantic code analysis library providing control flow graphs, data flow analysis, function purpose inference, and variable tracking

Semantic code analysis: ControlFlowAnalyzer, DataFlowAnalyzer, FunctionPurposeInference, VariableUsageTracker, composed as SemanticAnalyzer.

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@iris/code-tools

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Sandboxed code execution for agents: PythonRunner, TypeScriptRunner, ShellRunner over a code-executor/sandbox with output capture, composed as CodeTools.

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depends on@iris/types
lib

@iris/code-understanding

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Code intelligence system for deep multi-language code understanding with AST parsing, type inference, call graph analysis, and data flow tracking

Multi-language code intelligence: AstParser, SymbolExtractor, TypeInference, CallGraph, DataFlow, composed as CodeAnalyzer (the base the language analyzers extend).

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conversation-* (7)#

lib

@iris/conversation-branching

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Conversation branching system for exploring alternate dialogue paths

Conversation branching: BranchManager, BranchMerger, BranchSummarizer, BranchHistory for alternate dialogue paths.

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@iris/conversation-context

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Semantic context tracking for conversations including topics, entities, and context compression

Semantic context tracking: TopicDetector, EntityTracker, ContextCompressor, ContextSummarizer, composed as ContextTracker.

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@iris/conversation-core

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Core dialogue engine for managing multi-turn conversations

The core dialogue engine (~28 modules): ConversationManager (session lifecycle), TurnManager, ConversationHistory, context-window management, dialogue state, streaming response generator, plus search-index/bookmarks/highlights/tags/sharing and an in-memory storage backend.

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@iris/conversation-intent

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Intent recognition and classification system for conversations

Intent recognition (~36 modules): IntentClassifier, QuestionDetector, UrgencyDetector, SlotFiller, plus an extensive Direct-Command-Control (dcc-*) voice-session suite (intent decomposition, agent-delegation routing, voice confirmation/handoff, multi-user isolation).

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@iris/conversation-summarization

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Conversation summarization with incremental summaries, key points, and action items

Long-thread summarization: ConversationSummarizer, KeyPointExtractor, ActionItemExtractor (incremental summaries).

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@iris/conversation-templates

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Reusable conversation templates with variables, conditions, and branching

Reusable conversation templates: registry, variable substitution, conditional branching, a fluent builder, and TemplateExecutor.

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personalization-* (5)#

lib

@iris/personalization

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Comprehensive user modeling and personalization system for Iris AI

User-modeling and personalization (libs/iris/memory/personalization, ~30 modules): preference/interest/goal trackers, ExpertiseEstimator, BehaviorAnalyzer, Big-Five detection, context-fusion/prediction, location/device context, and a UserModelStore, composed as PersonalizationSystem.

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@iris/personalization-feedback

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Feedback learning system for personalization - collection, detection, processing, and adaptation

Feedback-learning for personalization (libs/iris/memory/personalization/feedback): FeedbackCollector, ImplicitFeedbackDetector, FeedbackProcessor, AdaptationEngine.

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@iris/personalization-inference

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Preference inference system for learning user preferences from behavioral signals

Preference inference: PreferenceInferrer, StyleAnalyzer, InterestDetector, ConfidenceTracker, composed as an InferenceSystem.

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@iris/personalization-segments

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User segmentation system for personalization clustering, defaults, and transition tracking

User segmentation: profile clustering/ranking, segment assignment with smoothing, segment-default behavior packs, and transition/stability metrics.

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privacy-* (5)#

lib

@iris/privacy

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Memory privacy and user control system for Iris AI

Memory privacy/user-control (libs/iris/memory/privacy, ~30 modules): memory viewer/editor/ deleter/exporter/importer, opt-out, consent manager, retention policy, PII redactor, differential privacy (noise injector, privacy budget), E2E encryption, key management, and a local store. (Note: distinct from the privacy/* tier libraries.)

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@iris/privacy-access

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Comprehensive access control, permissions, OAuth/OIDC integration, and audit logging for privacy-preserving AI systems

Access control (~9 modules): permissions/conditions engine, API-key management, OAuth2 + OIDC services, audit logging, and a rate limiter — the access-control layer for privacy-preserving systems.

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@iris/privacy-safety-behavior

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Behavioral safety and abuse prevention for AI systems

Behavioral safety/abuse prevention: action confirmation, sandboxed execution, rate limiting, and anomaly detection, composed as BehavioralSafety.

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@iris/privacy-safety-validation

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Output validation for AI safety including PII detection, bias detection, and factuality checking

Output validation: PIIDetector, BiasDetector, FactualityChecker, composed as an OutputValidationSystem.

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tool-* (5)#

lib

@iris/tool-composition

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Tool-workflow composition: ToolComposer, ToolPipeline, parallel executor, and conditional branching for complex tool graphs.

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@iris/tool-versioning

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Tool version/migration management with a real semver implementation (parseSemver, compareSemver, satisfiesConstraint), ToolMigrationUtils, deprecation handling, and a compatibility checker.

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vision-* (5)#

lib

@iris/multimodal/vision

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Production footage analysis facade for Iris multimodal vision tools

Thin V1 facade. Single index.ts for a production-footage analysis surface — metadata, IrisVision* types, default required-domains/quality-profile, and create*/validate*/ serialize* packet functions — not the vision engines (those are the vision-* libs).

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@iris/vision-documents

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Document parsing and analysis for the Iris AI domain

Document parsing: PDF/form/receipt/table extraction and layout analysis via a DocumentParser, with a large helper surface (currency formatting, bounding-box math, reading-order sorting, tableToCSV).

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@iris/vision-generation

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Image generation and editing module for Iris multimodal AI

Image generation/editing: a generation-impl with image creation, edit operations, diagram generation, and screenshot annotation, plus color/aspect-ratio/file-size helpers and model/ format constant tables.

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@iris/vision-understanding

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Comprehensive image understanding including object detection, scene description, OCR, and chart interpretation

Image understanding: object detection, scene description, OCR (50+ languages), and chart interpretation via an ImageAnalyzer, with IoU/bounding-box math and OCR-language tables.

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@iris/vision-video

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Video understanding module for Iris multimodal AI

Video understanding: a VideoAnalyzer for analysis, action recognition, temporal reasoning, summarization, and key-frame extraction, with timestamp/frame-rate/bitrate helpers and codec/resolution tables.

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everything else (26)#

lib

@iris/agent-builder

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Custom agent builder framework for Iris AI Assistant

Custom-agent builder framework (libs/iris/platform/customization/agents, ~21 modules): AgentBuilder, ToolBuilder, PersonaBuilder, a TemplateRegistry with built-in templates, plus template marketplace/installer/publisher/rating and a creation wizard.

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@iris/agents

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Mobile-safe Iris agent umbrella catalog for built-in assistant agents and launch readiness.

Thin V1 facade. Single index.ts exposing the built-in-agent catalog (listIrisBuiltInAgents, getIrisBuiltInAgent), capability/intent types, selectIrisAgentForIntent, and a launch-readiness resolver — a product-surface descriptor layer over the real agents-* runtime libs.

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@iris/agents-core

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Core agent framework for Iris AI - runtime, lifecycle, context, communication, and permissions

The agent runtime framework (~36 modules): context/lifecycle/communication/permission managers, AgentRuntime, AgentSystem, a tool-registry, provider adapters, a cognition gateway, budget, reward/recommendation models, execution replay/learning, and an oshun-ai-bridge. The substantive heart of the agents tier.

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@iris/analytics

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Analytics system for the Iris AI Assistant framework with privacy-compliant collection, metrics aggregation, and retention policies

Privacy-compliant analytics engine (~14 modules): analytics-engine, event-tracker, metrics-aggregator, retention/usage/quality, plus launch-monitoring, incident-response, and a runbook-executor.

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@iris/api-tools

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API-integration tools for agents: APIClient, RateLimiter, OAuthHandler (with OAuthProviders), ResponseParser, composed as APITools.

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depends on@iris/types
lib

@iris/concordia-assistant

#

Iris intake agent for Concordia — trauma-aware, multilingual, authority-aware private intake (Phase 179.3.1).

Iris intake state machine for the Concordia mediation domain (§179.3.1, Phase 179, ~21 source modules): trauma-/coercion-aware safety-signal detection and a runSafetyPipeline routing to Kuanyin restorative circles, hard-boundary gates, multi-device/party-isolated intake, language detection/drift, and human-reviewer queues.

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@iris/consistency

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Self-consistency checking with contradiction detection, belief tracking, and repair

Self-consistency checking: ContradictionDetector, BeliefTracker, ConsistencyRepair, composed as ConsistencyChecker/ConsistencySystem with quick-check helpers.

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@iris/embeddings

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The canonical embedding client for Oshun: a three-tier facade (tier1 OpenAI text-embedding-3-large, tier2 Voyage voyage-3-large, tier3 local BGE-M3) with cache/ disk-cache, metrics, migration, evaluation, an in-process embedder, and a multilingual benchmark. Decision-doc-grounded (docs/releases/p2/embeddings-provider-decision.md).

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@iris/filesystem-tools

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File system tools for Iris AI agents - read, write, search, watch

File-system tools: PermissionChecker, FileReadTool/FileWriteTool/FileSearchTool, DirectoryTool, FileWatchTool, composed as FileSystemTools.

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@iris/function-calling

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Function-calling framework: ParameterParser, ResultHandler, ErrorHandler, TimeoutManager, FunctionCaller, composed as FunctionCallingSystem.

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@iris/iot

#

IoT integration module for smart home and sensor integration

IoT/smart-home integration: device control across HomeKit/Google-Home/Alexa/SmartThings, room/scene management, automation rules, and sensor data, with extensive platform/device/ sensor constant tables and unit-conversion helpers.

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@iris/knowledge-rag

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Production-grade RAG (Retrieval Augmented Generation) pipeline for Iris

Production-grade RAG pipeline: query processing (expansion/decomposition/HyDE), hybrid retrieval with an in-memory BM25 index + RRF fusion, cross-encoder reranking, response generation, caching, and evaluation, composed as DefaultRAGPipeline.

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@iris/knowledge-types

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Knowledge type handling for factual, procedural, conceptual, and experiential knowledge

Knowledge type system: factual/procedural/conceptual/etc. types, a knowledge-factory, confidence scoring, retrieval strategies, and Zod type schemas.

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@iris/math-reasoning

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Mathematical reasoning with symbolic computation, equation solving, unit conversion, and statistical analysis

Mathematical reasoning: expression parse/eval, symbolic computation, EquationSolver, UnitConverter (dimensional analysis), StatisticalReasoner, composed as MathReasoner.

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@iris/memory-semantic

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Semantic memory system for knowledge graphs, concepts, and reasoning

Semantic memory: knowledge graphs, ConceptUnderstanding, RelationshipTracker, DomainExpertiseModel, UserKnowledgeGraph, SemanticInference, composed as SemanticMemory.

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@iris/metacognition

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Metacognitive monitoring with confidence calibration, knowledge gap detection, and learning opportunity identification

Metacognitive monitoring: ConfidenceCalibration, KnowledgeGapDetector, LearningOpportunityIdentifier, composed as MetacognitiveMonitor.

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@iris/multimodal/voice

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Production voice command facade for Iris multimodal voice tools

Thin V1 facade. Single index.ts for a production voice-command surface — metadata, IrisVoiceProduction* types, default command definitions routing to drone-fleet/switcher/ recorder, and packet create*/validate*/serialize* functions — not the voice engines.

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@iris/platform-sla-management

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Enterprise SLA management for Iris platform

Enterprise SLA management: an sla-manager for contract tracking, breach detection, incident management, and compliance reporting (barrel re-exports sla-manager/types).

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@iris/presence-integration

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Cross-service integration with Oshun ecosystem for Iris presence

Cross-service presence integration: per-domain integrations (Maya/Yemaya/Hathor/Nyx + a generic Oshun one) composed as UnifiedOshunIntegration.

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@iris/presence-sync

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Cross-device synchronization for seamless Iris presence experience

Cross-device presence sync: ConversationContinuityManager, TaskHandoffManager, NotificationUnificationManager, PreferenceSyncManager, StateSyncManager, composed as PresenceSyncManager.

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@iris/scientific-reasoning

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Scientific reasoning library for research-grade analysis, hypothesis generation, citation validation, and experiment design

Scientific reasoning: ScientificReasoner, CitationValidator, HypothesisGenerator, ExperimentDesigner, and retraction services.

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@iris/spatial

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AR/XR spatial computing (Vision Pro/Quest/Android XR/HoloLens): XR session management, spatial anchors, eye/gaze + hand-tracking, plane detection, and a real 3D-math toolkit (createPose, rayPlaneIntersection, raySphereIntersection, bounding-box ops).

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@iris/structured-reasoning

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Formal structured reasoning with logic validation, premise tracking, and inference

Formal structured reasoning: PremiseTracker, LogicValidator, ConclusionDeriver, ReasoningExplainer, composed as StructuredReasoner.

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@iris/tools-registry

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Tool registry system for agent tool management

Tool registry: schema management, ToolValidation, ToolDiscovery, and versioning, composed as ToolRegistrySystem.

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@iris/voice-providers

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Voice provider abstraction, voice-cloning workflow, watermark integrity, abuse-detection (§24.7)

Voice provider/profile layer (libs/iris/voice): a provider registry, a profile-registry, voice cloning workflow, and integrity tooling (watermark.ts, abuse detection) — barrel re-exports providers/cloning/integrity.

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@iris/web-tools

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Web browsing tools for Iris AI agents - search, fetch, scrape, navigate, forms

Web browsing tools for agents: HttpClient, ContentParser, and Search/Fetch/Scrape/ Navigate/Form tools with URL validation, composed as WebTools.

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infra (1)#

lib

@iris/config

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Configuration management for the Iris AI Assistant framework

Configuration management: model-provider config (Anthropic/OpenAI/Google), MemGPT-style hierarchical memory config, voice (STT/TTS/VAD) config, privacy settings, and a feature-flag system with a loader.

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testing (1)#

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@iris/testing

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Test utilities and mocks for Iris AI Assistant

The Iris test-utilities library (~30 modules): mock model/memory providers, fixtures, conversation/user factories, assertions, benchmarks, and API/event-contract + bias/ factuality/consistency/latency/load test helpers — the shared testing toolkit for the area.

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unclassified (186)#

accessibility-* (4)#

library

@iris/accessibility-adaptive

#

Adaptive UI engine with capability detection and preference sync

Adaptive-UI accessibility engine (adaptive-ui-engine.ts, interface-adapter.ts, user-capability-detector.ts, preference-sync.ts) that detects user capabilities and adapts the interface and syncs preferences. Real implementation, ~8 modules.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/accessibility-braille

#

Braille output, input, formatting, and display integration for accessibility

Braille support: BrailleFormatting, BrailleOutput, BrailleInput, and braille-display-integration.ts for refreshable-display I/O and braille translation.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/accessibility-testing

#

Automated and manual accessibility testing toolkit

Accessibility test tooling: AutomatedA11yChecks, A11yReporter, A11yTestSuite, and a manual-checklist generator for verifying a11y compliance.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/accessibility-voice-ui

#

Voice-first accessibility interface framework with menus, navigation, and feedback

Voice-driven UI framework: VoiceNavigation, VoiceFeedback, voice-menus.ts, composed by createVoiceUIFramework.

buildtestlint
scope: irisowner: @GreyChimp

agent-* (3)#

library

@iris/agent-marketplace

#

Marketplace primitives for agent packages: AgentMarketplace, AgentPublisher, AgentInstaller, AgentRating (publish/discover/install/rate).

buildtestlint
scope: irisowner: @GreyChimp

analytics-* (4)#

bci-* (4)#

lib

@iris/bci

#

Brain-Computer Interface preparation layer for IRIS multimodal system

Brain-computer-interface preparation layer (libs/iris/multimodal/bci): device abstraction, neural-signal processing, intent prediction, thought-action mapping, composed as BCISystem, with frequency-band helpers and an isBCIAvailable capability probe.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/bci-apple-hid

#

Apple BCI HID protocol support with intent decoding, thought-action mapping, and calibration flow

Apple BCI-over-HID integration: AppleBCIHIDListener, IntentSignalDecoder, ThoughtToActionMapper, BCICalibrationFlow, composed as AppleBCIHIDEngine.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/bci-intent-prediction-api

#

BCI intent prediction API with confidence scoring, ambiguity resolution, confirmation flow, and feedback learning

BCI intent prediction: IntentPredictionModel, ConfidenceScorerBCI, AmbiguityResolver, confirmation flow, feedback loop, and a fromAppleBCIFrame feature-vector adapter.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/bci-privacy-framework

#

Privacy and rights framework for BCI processing with minimization, consent, deletion, and auditing

Neural-data privacy: NeuralDataMinimization, MentalPrivacyProtection, NeuralDataDeletion (+ in-memory store), BCIAuditTrail, cognitive-liberty consent, and a BCIPrivacyFramework with ProtectedInferenceResult.

buildtestlint
scope: irisowner: @GreyChimp

code-* (20)#

library

@iris/code-architecture

#

Architecture intelligence for pattern detection, coupling analysis, and visual modeling

Architecture analysis: ArchitectureAnalyzer, PatternDetector, CouplingAnalyzer, and ArchitectureVisualizer for structural artifacts.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/code-cli

#

Iris CLI coding assistant with git workflow, build automation, deployment assistance, and log analysis

CLI coding assistant (~25 modules): a bin.ts entry, cli-assistant, git workflow (PRGenerator, ReviewAnalyzer, commit-generator, conflict-resolver), build/deploy assistance, log analysis, and createCLI.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
lib

@iris/code-codebase

#

Codebase understanding and repository analysis for Iris code intelligence

Codebase analysis: RepoAnalyzer, ArchitectureInference, DependencyAnalyzer, PatternDetector, and CodebaseIndexer/CodebaseSearch, composed as CodebaseAnalyzer.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
lib

@iris/code-consistency

#

Code consistency checking for style, naming, patterns, and API consistency

Code-consistency checking: StyleConsistencyChecker, NamingConventionEnforcer, PatternChecker, APIConsistencyChecker with quick-scan helpers and a combined analyzer.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
library

@iris/code-dependencies

#

Dependency intelligence for analysis, vulnerability scanning, update planning, and license compliance

Dependency intelligence: declaration analysis, VulnerabilityScanner, UpdateSuggester, LicenseChecker (license-policy validation).

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/code-explanation

#

Code explanation and understanding tools

Educational code explanation: CodeExplainer, step walkthroughs, ConceptExtractor, DiagramGenerator.

buildtestlinttypecheck
scope: sharedowner: @GreyChimp
lib

@iris/code-ide

#

IDE integration layer for AI code assistance - supports VSCode, JetBrains, Neovim, and Emacs

IDE integration layer: a BaseIDEAdapter with concrete VSCode/JetBrains/Neovim/Emacs adapters, JSON-RPC, inline-suggestions/chat/code-action services, plus detectIDEEnvironment and createAutoDetectedAdapter.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
library

@iris/code-ide-actions

#

AI-powered IDE code actions for fixes, refactors, and generation workflows

IDE code actions: CodeActionProvider, FixActions, RefactorActions, GenerateActions.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/code-ide-completions

#

Smart code completion engine for context-aware and multi-line IDE suggestions

Smart completions: context-aware and multi-line completions, completion explanation, and a SmartCompletionProvider.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/code-ide-hover

#

Smart IDE hover information with docs, types, and contextual explanations

Editor hover: DocumentationHover, TypeHover, ExplanationHover, and a SmartHoverProvider.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/code-ide-inline

#

Inline chat UX primitives for in-editor AI conversations

In-editor inline chat: ContextualSuggestions, QuickActions, InlineExplanation, and an inline-chat-widget.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/code-languages

#

Language-specific code analyzers for major programming languages

Per-language analyzers extending code-understanding — TypeScript, Python, Java, Go, Rust, C++, SQL, GraphQL — selected via createLanguageAnalyzer/hasLanguageAnalyzer.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
library

@iris/code-memory-persistence

#

Persistent coding memory with style profiling, preference inference, project context persistence, and convention enforcement

Coding-style memory: PreferenceInferrer, CodingStyleMemory (+ in-memory store), CodeConventionEnforcer, project-context persistence, composed as CodingMemoryPersistenceEngine.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/code-metrics

#

Code quality metrics including complexity, maintainability, and technical debt scoring

Code metrics: CodeMetricsCollector, ComplexityScorer, MaintainabilityScorer, technical-debt-calculator.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/code-quality

#

Code-quality analysis: SecurityVulnerabilityDetector, PerformanceOptimizer, BestPracticeEnforcer, TechnicalDebtIdentifier, CodeReviewer, plus quick-scan helpers and a combined QualityAnalyzer.

buildtestlint
scope: sharedowner: @GreyChimp
library

@iris/code-repository-intelligence

#

Repository-scale code understanding with indexing, dependency graphing, architecture inference, and multi-file reasoning

Repository intelligence: RepositoryIndexer, DependencyGraphBuilder, ArchitectureInferrer, ConventionDetector, MultiFileReasoner, composed as RepositoryIntelligenceEngine.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/code-review

#

Automated code review assistant with diff analysis, issue detection, and actionable suggestions

Automated code-review pipeline: DiffAnalyzer, IssueDetector, SuggestionGenerator, ReviewCommentFormatter, composed as CodeReviewAssistant.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/code-turbo-mode

#

Autonomous terminal execution with safety validation, permission gating, failure interpretation, and iterative fixes

Autonomous terminal execution: CommandSafetyValidator, AutonomousTerminalExecutor, ExecutionResultInterpreter, an IterativeFixLoop, and a turbo-mode permission manager.

buildtestlint
scope: irisowner: @GreyChimp

computer-* (5)#

library

@iris/computer-use-accessibility

#

Accessibility-first automation primitives: SemanticUINavigation, A11yTreeInspector, robust-element-selection.ts, accessibility-api-integration.ts for tree-aware desktop control.

buildtestlint
scope: irisowner: @GreyChimp

conversation-* (19)#

library

@iris/conversation-benchmarking

#

Model benchmarking: latency/quality/cost benchmarks and a BenchmarkSuite (with a mock model invoker) plus a reporter.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/conversation-citations

#

Citation and attribution system for Iris conversational AI - source tracking, inline citations, reference formatting, and fact checking

Citation/attribution: CitationTracker, SourceAttributor, ReferenceFormatter, FactChecker for inline citations and source tracking.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/conversation-costs

#

LLM cost tracking: CostTracker, BudgetManager, CostAlerting, CostReporting.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/conversation-export

#

Export conversations in multiple formats (Markdown, PDF, JSON, HTML)

Conversation export: Markdown/HTML/JSON/PDF exporters composed as ConversationExporter.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/conversation-finetuning

#

Model fine-tuning infrastructure for custom model training and management

Fine-tuning infrastructure: DataCollector, JobManager, ModelVersionManager, finetuning-metrics.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/conversation-format

#

Multi-format response formatting system for Iris conversational AI with specialized formatters for text, markdown, code, structured data, and media

Multi-format response formatting: text, markdown, code, structured-data, and media formatters.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/conversation-prompts

#

Prompt management: PromptLibrary, PromptVersioning, PromptTesting (with calculateSampleSize), PromptOptimizer.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/conversation-providers-anthropic

#

Anthropic Claude provider integration for Iris conversation system

Anthropic Claude provider adapter (anthropic-provider.ts + orchestration-adapter.ts): chat/streaming/tool-use/vision/extended-thinking support and a default-config factory, plugging into the orchestrator.

buildtestlint
scope: sharedowner: @GreyChimp
lib

@iris/conversation-providers-google

#

Google Gemini provider integration for Iris conversation system

Google Gemini provider adapter: chat with system instructions, multimodal inputs, function calling, streaming, and an orchestration adapter.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/conversation-rag

#

RAG integration for conversation response generation with context injection, source tracking, and fallback strategies

RAG integration for response generation: RAGPipeline with ContextInjector, SourceTracker, RelevanceScorer, and RAGFallback (plus a high-quality preset).

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/conversation-response

#

Response generation pipeline for conversational AI with streaming, validation, and multi-format support

Response-generation pipeline: ResponseGenerator, PromptBuilder, ResponseParser, ResponseValidator, ResponseFormatter, and streaming response support.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/conversation-state

#

Advanced state management for dialogue systems with guards, rollback, and branching

Advanced dialogue-state management: guard-evaluated state machines, CheckpointManager (persistence/recovery), BranchManager (exploration), composed as StateManager.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/conversation-style

#

Style adaptation system for Iris AI assistant - tone detection, formality control, personality matching, and style learning

Style adaptation: ToneDetector, FormalityController, PersonalityMatcher, StyleLearner, composed as StyleAdapter.

buildtestlint
scope: irisowner: @GreyChimp
depends on@oshun/logging
library

@iris/conversation-tokens

#

Token optimization: TokenCounter/SimpleTokenizer, TokenOptimizer, ContextCompressor, TokenBudgetManager.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/conversation-uncertainty

#

Uncertainty quantification system for Iris conversational AI - confidence estimation, hedging language, clarification generation, and knowledge boundary detection

Uncertainty quantification: ConfidenceEstimator, UncertaintyExpressor (hedging), ClarificationGenerator, KnowledgeBoundary detection.

buildtestlint
scope: sharedowner: @GreyChimp

emotional-* (9)#

lib

@iris/emotional-multimodal-fusion

#

Advanced multimodal emotion fusion with text/voice analysis, contextual interpretation, and longitudinal tracking

Multimodal emotion fusion: TextEmotionAnalyzer, VoiceEmotionAnalyzer, EmotionFusionEngine, ContextualEmotionInterpreter, EmotionHistoryTracker, composed as MultimodalEmotionAnalyzer.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
lib

@iris/emotional-recognition

#

Multi-modal emotion recognition system with text sentiment analysis, voice emotion detection, and multimodal fusion

Multi-modal emotion recognition: EmotionRecognizer, TextSentimentAnalyzer, VoiceEmotionAnalyzer, MultimodalFusion.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
lib

@iris/emotional-voice-analysis

#

48-category affective voice emotion analysis with prosodic modeling and temporal micro-shift detection

Prosody-based voice emotion analysis: ProsodEmotionAnalyzer, a 48-class Emotion48Classifier, confidence/temporal tracking, micro-emotion detection, composed as VoiceEmotionAnalysisEngine.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
lib

iris/emotional-ethics

@iris/emotional-ethics#

Ethical boundaries for emotionally-aware AI - identity clarity, relationship respect, transparency, and crisis protocols

Non-negotiable ethical boundaries for emotionally-aware AI: AIIdentityClarity, CapabilityTransparency, CrisisProtocol, MandatoryReferral, human-relationship respect, composed as EthicalBoundaries. (Project name lacks the @ prefix.)

buildtestlinttypecheck
scope: irisowner: @GreyChimp
lib

iris/emotional-rapport

@iris/emotional-rapport#

Rapport building and relationship management for emotionally-aware AI

Rapport building: TrustIndicators, RelationshipProgress, personalized interaction, composed as RapportBuilder. (Name lacks @ prefix.)

buildtestlinttypecheck
scope: irisowner: @GreyChimp
lib

iris/emotional-response

@iris/emotional-response#

Emotionally adaptive response generation for Iris

Emotionally-adaptive response generation (~16 modules): EmotionalAdapter, ToneMatcher, DeEscalator, Celebrator, Supporter, plus crisis-support/stress-management/mindfulness/ gratitude-journal/wellbeing-report modules with named default configs. (Name lacks @.)

buildtestlinttypecheck
scope: irisowner: @GreyChimp
lib

iris/emotional-social

@iris/emotional-social#

Social intelligence library for culturally aware, socially appropriate AI interactions

Social intelligence: CulturalAwareness, FormalityCalibrator, HumorCalibrator, BoundaryRespect, SocialCueDetector, composed as SocialIntelligence. (Name lacks @.)

buildtestlinttypecheck
scope: irisowner: @GreyChimp
lib

iris/emotional-tracking

@iris/emotional-tracking#

Longitudinal emotion tracking and pattern analysis

Longitudinal emotion tracking: MoodTracker, PatternAnalyzer, TrendAnalyzer over time. (Name lacks @ prefix.)

buildtestlinttypecheck
scope: irisowner: @GreyChimp
lib

iris/emotional-wellbeing

@iris/emotional-wellbeing#

Consent-based wellbeing monitoring for emotionally-aware AI

Consent-based, explicitly non-diagnostic wellbeing monitoring: GentleCheckIn, ResourceSuggester, ConcerningPatternDetector, ProfessionalReferral, composed as WellbeingMonitor. (Name lacks @ prefix.)

buildtestlinttypecheck
scope: irisowner: @GreyChimp

integrations-* (6)#

integration

@iris/integrations-hathor

#

Hathor Worldbuilding integration for Iris AI Platform

Integration adapter to the Hathor worldbuilding domain: lore context, WorldKnowledgeService, CharacterDatabaseService, TimelineNavigationService, LoreConsistencyChecker, plus lore-keeper/plot-advisor/world-consistency agents (~22 modules).

buildtestlinttypecheck
scope: irisowner: @GreyChimp
integration

@iris/integrations-maya

#

Iris AI integration with Maya metaverse engine

Integration to the Maya metaverse engine: in-world MayaCompanion, WorldContextManager, SpatialVoiceChat, WorldCommands, plus world-builder/npc-control/asset-creator agents and personality presets.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
integration

@iris/integrations-nyx

#

Nyx Astronomy integration for Iris AI Platform

Integration to the Nyx astronomy domain: celestial-guide/event/educational services and stargazer/observation-planner/astronomy-tutor agents, composed by createNyxIntegration.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
integration

@iris/integrations-psyche

#

Iris integration with Psyche domain for AI avatar representation, emotion expression, and conferencing presence

Integration to the Psyche domain for AI-avatar presence: avatar/conferencing/emotion services and presenter/participant/persona agents with a platform-adapter.

buildtestlint
scope: irisowner: @GreyChimp
integration

@iris/integrations-sophia

#

Sophia Research & Knowledge integration for Iris AI Platform

Integration to the Sophia research/knowledge domain: research-assistant, knowledge-base, literature-search, and citation-manager services + agents, composed by createSophiaIntegration.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
lib

@iris/integrations-yemaya

#

Iris AI Platform integration with Yemaya Creative Studio

Integration to the Yemaya creative-studio domain (~27 modules): project-context, asset-understanding, creative-suggestions, and workflow-automation services + agents (asset- organizer/audio-mixer/video-editor/design-assistant).

buildtestlint
scope: irisowner: @GreyChimp

knowledge-* (21)#

lib

@iris/knowledge

#

Iris Knowledge System - Unified knowledge management with source registry, indexing, freshness, and quality scoring

The unified knowledge system (libs/iris/knowledge/core, ~18 modules): source registry, indexing, quality/freshness scoring, conflict detection, citation formatting, federation, marketplace/monetization, and source-credibility ranking, with capability probes (isKnowledgeAvailable).

buildtestlinttypecheck
scope: irisowner: @GreyChimp
library

@iris/knowledge-agentic-rag

#

Agentic retrieval orchestration for autonomous strategy adaptation in Iris RAG

Agentic retrieval orchestration: QueryDecomposer, RetrievalStrategySelector, IterativeRefinement, SourceQualityAssessor, dense/sparse/graph retrievers + fusion + evaluator, plus an EmbeddingDenseRetriever, composed as RetrievalAgent.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/knowledge-chunking

#

Intelligent document chunking for RAG systems

Document chunking for RAG: semantic/hierarchical/code chunkers, table/figure extractors, and a ChunkingPipeline, with Zod-validated config.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/knowledge-curation

#

Knowledge curation with duplicate detection, quality scoring, and merge workflows

Knowledge curation pipeline: DuplicateDetector, QualityScorer, KnowledgeMerger, composed as KnowledgeCurator.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/knowledge-embeddings

#

Embedding-service abstraction with OpenAI/Cohere/local providers, an EmbeddingCache, batch processing, and similarity calculations.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/knowledge-enterprise

#

Enterprise knowledge integration connectors for Iris

Enterprise knowledge connectors: Confluence/Notion/SharePoint/Google-Drive connectors over a BaseConnector with a ConnectorFactory and OAuth2/API-token auth.

buildtestlint
scope: irisowner: @GreyChimp
depends on@iris/knowledge
library

@iris/knowledge-export

#

Knowledge base export utilities for JSON-LD, RDF, and wiki formats

Knowledge export: JSON-LD, RDF, and Wiki exporters composed as KnowledgeExporter (linked- data / semantic-web formats).

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/knowledge-factcheck

#

Automated fact checking pipeline with claim extraction, evidence retrieval, and veracity scoring

Automated fact-checking: ClaimExtractor, EvidenceRetriever, SourceCredibilityScorer, VeracityScorer, composed as FactChecker.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/knowledge-freshness

#

Knowledge freshness tracking, temporal relevance scoring, and change notification system

Freshness tracking: FreshnessTracker, TemporalRelevanceScorer, VersionTracker, ChangeNotifier, continuous index updater, composed as a UnifiedFreshnessSystem.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
library

@iris/knowledge-graph

#

Knowledge graph storage, extraction, querying, and visualization for entities and relationships

Knowledge-graph stack: EntityExtractor, RelationshipExtractor, KnowledgeGraphStore, GraphQueryEngine, GraphVisualization, and an ingestTextIntoKnowledgeGraph pipeline.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/knowledge-graphrag

#

GraphRAG knowledge graph retrieval and multi-hop reasoning pipeline for Iris

GraphRAG: KnowledgeGraphBuilder, community detection, GraphSummarizer (hierarchical), a GraphRAGQueryEngine (multi-hop), composed as GraphRAGPipeline.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/knowledge-grounding

#

Grounding and attribution system for AI-generated content with claim extraction, source citation, confidence scoring, fact verification, contradiction detection, and hallucination detection

Grounding/attribution for AI output: claim extraction, source citation, confidence scoring, fact verification, contradiction + hallucination detection, composed as DefaultGroundingPipeline.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
lib

@iris/knowledge-personal

#

Iris Personal Document Indexing - File watching, format handling, metadata extraction, and PII detection for personal documents

Personal document indexing: DocumentIndexer with file watcher, format handler, metadata extractor, change tracker, and a privacy filter, integrating with @iris/knowledge.

buildtestlint
scope: irisowner: @GreyChimp
depends on@iris/knowledge
library

@iris/knowledge-query

#

Comprehensive query expansion and reformulation system for RAG retrieval

Query expansion/reformulation for RAG: QueryExpander (synonym/semantic/entity/PRF/LLM), QueryReformulator, HyDE HypotheticalDocument, and a MultiQueryRetriever with fusion.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/knowledge-rag-adaptive-chunking

#

Adaptive chunking for RAG using content-aware sizing and quality scoring

Adaptive chunking: ContentTypeDetector, OptimalChunkSizer, ChunkQualityScorer, composed as AdaptiveChunker.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/knowledge-rag-debugging

#

RAG debugging toolkit with retrieval explanations, chunk inspection, and relevance visualizations

RAG observability: RetrievalExplainer, ChunkInspector, RelevanceVisualizer, composed as RAGDebugger.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/knowledge-rag-evaluation

#

RAG evaluation stack with retrieval, generation, and end-to-end quality metrics

RAG evaluation: retrieval/generation/e2e metrics and an EvaluationDashboard, composed as RAGEvaluator.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/knowledge-rag-multimodal

#

Multi-modal RAG retrieval for image, table, and code knowledge sources

Multi-modal retrieval: ImageRAG, TableRAG, CodeRAG, and a fusion-based ranker (MultiModalFusion).

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/knowledge-realtime

#

Real-time knowledge integration system with web search, news, academic papers, and social media monitoring

Real-time knowledge: web/news/academic search and social-media monitoring with a multi-engine aggregator, composed as a UnifiedKnowledgeSystem.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
library

@iris/knowledge-retrieval

#

Hybrid retrieval system combining dense and sparse retrieval with advanced reranking

Hybrid retrieval: dense (bi-encoder) + sparse retrievers, multiple fusion methods, ColBERT-style multi-vector retrieval, cross-encoder reranking, and evaluation metrics.

buildtestlint
scope: irisowner: @GreyChimp

memory-* (13)#

lib

@iris/memory-consolidation

#

Memory consolidation system for Iris - natural forgetting, importance scoring, and memory compression

Memory consolidation: forgetting-curve DecayAlgorithm, ImportanceScorer, SummaryGenerator, MemoryClusterer, composed as ConsolidationEngine.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/memory-debugging

#

Memory debugging tools for the Iris memory subsystem

Memory debugging: MemoryDebugger, retrieval explainer, timeline + change tracking, and a debug-session manager.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/memory-episodic

#

Iris episodic memory - event-based autobiographical memory with temporal context

Episodic memory: event-based autobiographical episodes with temporal context, a MemorableInteractionDetector, MilestoneTracker, task-completion records, and episodic retrieval.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/memory-long-term

#

Long-term memory (LTM) implementation for Iris AI agents with persistent storage and semantic retrieval

Long-term memory: persistent LongTermMemory, PreferenceStore, PatternStore, CorrectionStore, plus LTM consolidation/retrieval.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/memory-migration

#

Memory migration library for importing from ChatGPT, Claude, and custom AI systems

Memory import from external AI systems: ChatGPT/Claude/custom importers over a BaseMemoryImporter (with content hashing) and a migration pipeline.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/memory-retrieval

#

High-performance memory retrieval system with hybrid search, BM25, semantic matching, and multi-source fusion

High-performance memory retrieval (<100ms target): hybrid semantic + BM25 keyword search, temporal search, multi-factor relevance ranking, and multi-source fusion, composed as MemoryRetriever (with an embedding-service seam).

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/memory-sharing

#

Memory sharing library for access control, shared spaces, and collaborative synchronization

Memory sharing/collaboration: MemoryAccessManager, shared spaces, and synchronization services.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/memory-short-term

#

Short-term memory (STM) implementation for Iris AI agents

Short-term/working memory: ShortTermMemory, WorkingMemory, recent-references tracking, STM eviction, and temporal decay.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/memory-tools

#

LLM-callable memory management tools for Iris AI assistants

LLM-callable memory tools: tool definitions, handlers, and an executor for letting an assistant manage its own memory (with formatToolsForClaude).

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/memory-transitions

#

Memory tier transition system for Iris AI agents with promotion, demotion, and consolidation

Memory-tier transitions: MemoryPromoter (STM→LTM), MemoryDemoter (LTM→archival), ImportanceScorer, a consolidation scheduler, and transition metrics.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/memory-writing

#

Memory writing system for Iris AI agents with validation, merging, and conflict resolution

Memory writing: MemoryWriter, MemoryValidator, MemoryMerger (dedup), MemoryUpdater, and a conflict resolver with batch-write support.

buildtestlint
scope: irisowner: @GreyChimp

personalization-* (3)#

library

@iris/personalization-benchmarking

#

LCMP-style personalization benchmarking with metrics, stress testing, and regression detection

Personalization benchmarking (libs/iris/personalization/benchmarking): PersonalizationMetrics, ContextLengthStressTest, PersonalizationRegression, and an LCMPBenchmarkRunner.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/personalization-state-aware

#

State-aware personalization engine with concept tracking, variation detection, context windows, and continual learning

State-aware personalization: PersonalizedConceptTracker, VariationPerceiver, a personalization context window, StateAwareResponseGenerator, and a ContinualPersonalizationLearner, composed as StateAwarePersonalizationEngine.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/personalization-user-model-persistence

#

Persistent and portable user model persistence for state-aware personalization

User-model persistence: snapshot, versioning, migration, export, and privacy-controls modules over a user-model-persistence-service.

buildtestlint
scope: irisowner: @GreyChimp

platform-* (11)#

library

@iris/platform-admin

#

Enterprise admin console backend for Iris platform

Enterprise admin-console backend: EnterpriseAdminService with a default config. Small but real (3 modules).

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/platform-codegen

#

OpenAPI-based SDK code generator for Iris platform clients

SDK code generation: OpenAPIToSDK, TypeGenerator, ClientGenerator, composed as SDKCodeGenerator.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/platform-reporting

#

Enterprise reporting service for Iris platform

Enterprise reporting: EnterpriseReportingService with default metrics-by-type config. Small but real (3 modules).

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/platform-sdk-docs

#

SDK documentation generation toolkit for Iris platform SDKs

SDK documentation generation: CodeSampleGenerator, QuickstartGenerator, TutorialGenerator, composed as SDKDocGenerator.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/platform-sdk-testing

#

SDK integration, compatibility, and performance testing suite for Iris platform

SDK test tooling: IntegrationTests, CompatibilityTests, PerformanceTests, composed as SDKTestSuite.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/platform-sla

#

Enterprise SLA management for Iris platform services

Enterprise SLA management — a smaller sibling of platform-sla-management (barrel re-exporting sla-manager/types, 3 modules). Honest overlap: both expose an SLA manager; this one is the leaner variant.

buildtestlint
scope: irisowner: @GreyChimp

privacy-* (19)#

library

@iris/privacy-anonymization

#

Strong data anonymization toolkit with k-anonymity and l-diversity validation

Data anonymization: KAnonymity, LDiversity, a DataAnonymizer, and an anonymization validator, with real quasiKey/pseudonymize/generalizeValue utilities.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/privacy-audit

#

Privacy audit toolkit with compliance checks, reports, and remediation planning

Privacy audit: ComplianceChecker, AuditReportGenerator, RemediationSuggester, composed as PrivacyAuditor, with risk-scoring utilities.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/privacy-communication

#

Privacy-focused secure communication library - TLS enforcement, certificate pinning, secure WebSocket, and API gateway

Secure communication: TLSEnforcement, CertificatePinning, SecureWebSocket, and a SecureGateway.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
library

@iris/privacy-dashboard

#

Privacy dashboard primitives for inventory, consent, and deletion governance

Privacy dashboard: DataInventoryView, ConsentManagerUI, DeletionRequestsUI, composed as a PrivacyDashboardUI.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/privacy-encryption

#

End-to-end encryption library for Iris privacy module with encrypted storage, model I/O, zero-knowledge proofs, and secure multi-party computation

E2E encryption (~14 modules): crypto primitives (AES-256-GCM, ChaCha20-Poly1305, Ed25519), KeyManager (rotation/audit), Double-Ratchet E2E, encrypted storage/model-IO, secure MPC, and zero-knowledge proofs.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/privacy-local

#

Iris privacy-preserving local inference - on-device AI processing with Ollama and llama.cpp support

On-device AI inference (~23 modules): Ollama and llama.cpp runtimes, a ModelManager/ ModelOptimizer, GPU/NPU accelerator detection, offline cache/sync/features, and hybrid cloud/edge routing, composed as a LocalInferenceEngine.

buildtestlinttypecheck
scope: sharedowner: @GreyChimp
library

@iris/privacy-minimization

#

Data minimization toolkit with detection, retention enforcement, and automated purging

Data minimization: UnnecessaryDataDetector, DataMinimizer, RetentionEnforcer, AutoPurger, with end-to-end minimization reports.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/privacy-private-cloud

#

Private cloud compute layer with secure enclave processing, ephemeral execution, and no-retention guarantees

Private-cloud compute: SecureEnclaveProcessor, EphemeralProcessing, AuditableCompute, HardenedServerConfig (with a hardened baseline), NoDataRetention, composed as a PrivateCloudComputeLayer.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/privacy-safety-content

#

AI content safety library - content filtering, harmful content detection, jailbreak resistance, age-appropriate responses, toxicity detection

Content safety: multi-layer ContentFilter, HarmfulContentDetector, jailbreak resistance, age-appropriate responses, ToxicityDetector, composed as SafetyChecker.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
lib

@iris/privacy-safety-transparency

#

AI transparency features for identity disclosure, capability limitations, decision explanation, and uncertainty disclosure

AI transparency: identity disclosure, capability-limitation disclosure, DecisionExplainer, uncertainty disclosure, composed as TransparencySystem.

buildtestlinttypecheck
scope: irisowner: @GreyChimp
library

@iris/privacy-security-compliance

#

Compliance certification management for SOC2, HIPAA, GDPR, and ISO27001

Compliance certification for SOC2/HIPAA/GDPR/ISO27001 (ComplianceCertificationManager/createComplianceCertificationManager). Small (3 modules) but real.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/privacy-security-dlp

#

Data Loss Prevention service for scanning and protecting sensitive data

Data-loss prevention: a single data-loss-prevention module re-exported by the barrel. Thin (the smallest privacy-security lib) but real, not a scaffold.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/privacy-security-injection

#

Prompt injection and jailbreak defense with sanitization and adaptive response strategy

Prompt-injection defense: PromptInjectionDetector, JailbreakDetector, InputSanitizer, composed as DefenseStrategy.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/privacy-security-logging

#

Comprehensive security event, access, change, and alert logging

Security logging: SecurityLogger, AccessLogger, ChangeLogger, SecurityAlertLogger with default configs.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/privacy-security-pentest

#

Automated penetration testing suite with vulnerability scanning, fuzzing, and reporting

Penetration testing: VulnerabilityScanner, FuzzTester, SecurityReporter, composed as SecurityTestSuite.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/privacy-security-threats

#

Threat detection stack with abuse signatures, anomaly detection, and adaptive response

Threat detection: AbusePatternsDetector, behavioral AnomalyDetector, ThreatResponse, composed as ThreatDetector, with haversineKm/severity-weight utilities.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/privacy-sovereignty

#

Data sovereignty and compliance controls for Iris AI

Data sovereignty: data-residency controls, GDPR (Arts. 15-22/30/33-34) and CCPA/CPRA compliance modules, cross-border transfer, and right-to-deletion, with an extensive typed surface (residency/minimization/consent/analytics) and a DataSovereigntyManager.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/privacy-tiered-compute

#

Tiered privacy-aware compute routing with explicit consent and fallback governance

Tiered compute routing by sensitivity: ComplexityEstimator, PrivacySensitivityClassifier, UserConsentManager, TierRouter, TierFallbackChain, composed as TieredComputeOrchestrator.

buildtestlint
scope: irisowner: @GreyChimp

sdk-* (4)#

sdk

@iris/sdk

#

Official TypeScript/JavaScript SDK for the Iris AI Assistant API

The official TypeScript/JavaScript SDK (libs/iris/sdk/typescript): an IrisClient/Iris client with createClientFromEnv, conversation/agent/memory/knowledge sub-clients, and an HTTP layer (client.chat(...)).

buildtestlinttypecheck
scope: irisowner: @GreyChimp
sdk

@iris/sdk-kotlin

#

Kotlin SDK (libs/iris/sdk/kotlin): a Gradle module with IrisClient and Agent/Conversation/Knowledge/Memory clients, an HttpClient, typed Types.kt, and a client test — the JVM/Android client view of the Iris API.

buildtestcleanpublish
scope: irisowner: @GreyChimp
sdk

@iris/sdk-rust

#

Rust SDK (libs/iris/sdk/rust): a iris_sdk crate (lib.rs) with an async IrisClient, per-domain client modules (agent/conversation/knowledge/memory), an HTTP layer, typed errors/types — type-safe async access to the API.

buildtestlintcleandocfmtpublish
scope: irisowner: @GreyChimp
sdk

@iris/sdk-swift

#

Swift SDK (libs/iris/sdk/swift): a SwiftPM package (IrisSDK) with IrisClient, Agent/Conversation/Knowledge/Memory clients, an HTTPClient, typed Types.swift, and tests — the Apple-platform client.

buildtestcleanresolve
scope: irisowner: @GreyChimp

testing-* (4)#

library

@iris/testing-chaos

#

Chaos engineering toolkit for Iris platform reliability testing

Chaos testing: NetworkChaos, ServiceChaos, DataChaos, composed in a chaos-test framework.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/testing-load

#

Load testing toolkit for Iris reliability and performance validation

Load testing: ScenarioBuilder, LoadProfiler, LoadReporter, composed as a load-test suite.

buildtestlint
scope: irisowner: @GreyChimp

vision-* (4)#

voice-* (10)#

lib

@iris/voice

#

Speech recognition system with real-time STT, streaming transcription, voice activity detection, and multi-language support

Speech-recognition system (libs/iris/multimodal/voice/recognition, ~30 modules): real-time STT (SpeechRecognizer), streaming transcription, VAD, noise processing, accent/dialect handling, multilingual + code-switch detection, speaker diarization/identification/ verification, anti-spoofing, composed as VoiceRecognitionSystem.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/voice-conversation

#

Full-duplex voice conversation engine with natural turn-taking

Full-duplex voice conversation (~12 modules): a full-duplex-engine with VAD/turn-taking/ interruption/backchannel handling, prosody and emotion sub-modules, and WebRTC voice transport, with rich turn-completion helpers.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/voice-empathic-synthesis

#

Empathic voice synthesis adaptation with dynamic emotional mirroring and frustration de-escalation

Empathic voice synthesis (libs/iris/voice/empathic-synthesis): EmotionalToneAdapter, ProsodyModulator, EmpatheticMirroring, DynamicToneShift, FrustrationDeescalation, composed as EmpathicSynthesisEngine.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/voice-synthesis

#

Text-to-speech synthesis system with real-time TTS, voice selection, prosody control, and streaming synthesis

Text-to-speech (~20 modules): a SpeechSynthesizer with voice selection, prosody/emotion control, and streaming, plus concrete ElevenLabs/Cartesia/local/persona provider sub-modules, composed as SynthesisSystem.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/voice-ultra-low-latency

#

Sub-100ms streaming TTS pipeline with speculative preloading and dynamic quality-latency tradeoffs

Ultra-low-latency voice (~18 modules): a StreamingTTSPipeline, AudioBufferPreloader, LatencyMonitor, full-duplex interruption handling, endpointing/turn-taking/backchannel models, and a VoiceActivityOptimizationEngine, composed as UltraLowLatencyVoiceEngine.

buildtestlint
scope: irisowner: @GreyChimp

everything else (23)#

lib

@iris/a2a

#

Unmounted A2A-shaped compatibility prototype; not a conformant or deployable A2A implementation

Private, unmounted A2A-shaped compatibility prototype (libs/iris/a2a/src): local agent-card, task-negotiation, and result-sharing experiments only. It is not a current A2A implementation or interoperability claim. ADR-0091 defers adoption until a named independent agent boundary exists.

buildtestlint
scope: sharedowner: @GreyChimp
lib

@iris/action-safety

#

Action safety system for AI agents with validation, blocking, and audit logging

Action-safety system for agents: ActionValidator, DangerousActionBlocker, confirmation workflow, undo capability, and audit log, composed as SafetySystem.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/ambient

#

Ambient intelligence system with background monitoring and anomaly detection

Ambient intelligence (proactive): BackgroundMonitor, AnomalyDetector, OpportunityIdentifier, RiskAwareness, AlertManager, composed by AmbientIntelligenceSystem.

buildtestlint
scope: sharedowner: @GreyChimp
lib

@iris/anticipation

#

Anticipatory-assistance engine (~30 modules) — pattern recognition, context triggers, relevance scoring, need/task prediction, productivity-awareness (break/timing/focus), and opportunity detection — the largest proactive lib.

buildtestlint
scope: sharedowner: @GreyChimp
library

@iris/archetypes

#

Specialized agent archetypes for common task domains

Specialized agent archetypes (libs/iris/agents/archetypes) — Research/Code/Data/Creative/ Operations agents (aliased Researcher/Coder/Analyst/Writer/Operator) over a base-archetype.ts, with an ArchetypeRegistry and createArchetypeWithPersona. Includes real research-nlp.ts, web-search-provider.ts, command-runner.ts helpers.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/automation

#

Automation proposals system for identifying, suggesting, recording, and executing automations

Workflow-automation proposals: PatternBasedAutomation, AutomationSuggester, WorkflowRecorder, WorkflowManager, executed by AutomationSystem.

buildtestlint
scope: sharedowner: @GreyChimp
library

@iris/database-tools

#

Database tools for AI agents with safe query execution and exploration

Database tools for agents: QueryValidator, QueryBuilder, DatabaseBrowser, ResultFormatter, and a SQLQueryTool over a DatabaseExecutor seam (with a mock executor for tests).

buildtestlint
scope: irisowner: @GreyChimp
depends on@iris/types
library

@iris/desktop-automation

#

Quarantined simulated desktop prototype for tests; not a production or Eve runtime

Desktop application automation: DesktopController, WindowManager, MenuNavigator, DialogHandler, ShortcutExecutor, wrapped by DesktopAutomationAgent.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/learning-tools

#

Tool learning system for AI agents - parsing docs, inferring parameters, and optimizing usage patterns

Tool-learning system: ToolDocParser (OpenAPI/TypeScript), ParameterInference, UsagePatternOptimizer, dynamic tool registration, plus a real TDigest/PercentileTracker.

buildtestlint
scope: irisowner: @GreyChimp
depends on@iris/types
lib

@iris/model-routing

#

Intelligent model routing and selection for the Iris conversation system

Intelligent model routing/selection: TaskClassifier, CostOptimizer, LatencyOptimizer, QualityEstimator, and configurable RoutingPolicy, composed as ModelRouter (with balanced/cost presets).

buildtestlint
scope: sharedowner: @GreyChimp
lib

@iris/multi-agent

#

Multi-agent orchestration and coordination for AI agents

Multi-agent orchestration (~22 modules): AgentSpawner, InterAgentMessaging, TaskDistributor, ResultAggregator, SharedContext, plus consensus/negotiation/ handoff/conflict protocols and an orchestrator.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/plugins

#

Plugin architecture for extending Iris AI platform

Plugin architecture (~17 modules): PluginRegistry, PluginLifecycleManager, PluginSandbox, UI-extension/integration managers, and a plugin workflow engine, composed as PluginSystem.

buildtestlinttypecheckdev
scope: irisowner: @GreyChimp
lib

@iris/reasoning-thinking

#

Extended thinking and chain-of-thought reasoning for Iris AI

Extended-thinking / chain-of-thought: ThinkingMode, ReasoningChain, ThoughtValidator, ThinkingBudget, and a thinking-summary generator.

buildtestlint
scope: sharedowner: @GreyChimp
lib

@iris/reminders

#

Schedule-aware reminder system with calendar integration and smart timing

Schedule-aware reminders: SmartTiming, DeadlineTracker, calendar integration/sync, and a multi-channel ReminderEngine with a DeliveryProvider seam.

buildtestlint
scope: sharedowner: @GreyChimp
lib

@iris/sandbox

#

Sandboxed execution environment for AI agents with isolation and resource limits

Sandboxed execution environment: ResourceManager (with TokenBucket), NetworkController, FilesystemController, SnapshotManager, plus SandboxEnvironment/ SandboxManager for isolated agent execution.

buildtestlint
scope: irisowner: @GreyChimp
lib

@iris/streaming

#

Streaming APIs for Iris AI Assistant - SSE, WebSocket, and gRPC

Streaming APIs (libs/iris/platform/streaming): SSE, WebSocket, and a gRPC-streaming abstraction behind a ProtocolFactory, composed as StreamingManager with createStreamingClient.

buildtestlint
scope: irisowner: @GreyChimp
library

@iris/whitelabel

#

White-label customization support for Iris AI platform

White-label customization (~24 modules): brand/theme/voice-persona/deployment builders + managers, a component registry, preset themes/voices, custom-domain support with a dns-resolver and ssl-provisioner.

buildtestlinttypecheckdev
scope: irisowner: @GreyChimp
lib

@iris/workflows

#

Workflow orchestration for AI agent task sequences

Workflow orchestration (~17 modules): WorkflowEngine (with a TaskExecutor seam), TaskDecomposer, DependencyGraph, ProgressTracker, ErrorRecovery, parallel executor, plan visualizer.

buildtestlint
scope: irisowner: @GreyChimp
sdk

iris-sdk-python

#

Python SDK (libs/iris/sdk/python): an iris_sdk package with IrisClient, per-domain clients (agent/conversation/knowledge/memory), http.py, typed types.py, and py.typed, packaged via pyproject.toml. (Project name lacks the @iris/ prefix.)

buildtestlinttypecheckformat
scope: irisowner: @GreyChimp