hindsight-docs
Provides comprehensive Hindsight documentation for AI agents, aiding in understanding and analyzing AI behavior, optimizing decision-making, and enhancing system transparency.
npx skills add https://github.com/vectorize-io/hindsight --skill hindsight-docsBefore / After Comparison
1 组When an AI agent performs complex tasks, it often lacks long-term memory and context understanding, easily forgetting previous conversations or decisions, leading to low task execution efficiency or logical errors.
By integrating the Hindsight memory system, the AI agent gains powerful biomimetic memory capabilities. It can store, retrieve, and associate large amounts of information, thereby maintaining contextual coherence and making smarter decisions during long-term interactions and complex tasks.
Hindsight Documentation Skill
Complete technical documentation for Hindsight - a biomimetic memory system for AI agents.
When to Use This Skill
Use this skill when you need to:
- Understand Hindsight architecture and core concepts
- Learn about retain/recall/reflect operations
- Configure memory banks and dispositions
- Set up the Hindsight API server (Docker, Kubernetes, pip)
- Integrate with Python/Node.js/Rust SDKs
- Understand retrieval strategies (semantic, BM25, graph, temporal)
- Debug issues or optimize performance
- Review API endpoints and parameters
- Find cookbook examples and recipes
Documentation Structure
All documentation is in references/ organized by category:
references/
├── developer/
│ ├── api/ # Core operations: retain, recall, reflect, memory banks
│ └── *.md # Architecture, configuration, deployment, performance
├── sdks/
│ ├── *.md # Python, Node.js, CLI, embedded
│ └── integrations/ # LiteLLM, AI SDK, OpenClaw, MCP, skills
└── cookbook/
├── recipes/ # Usage patterns and examples
└── applications/ # Full application demos
How to Find Documentation
1. Find Files by Pattern (use Glob tool)
# Core API operations
references/developer/api/*.md
# SDK documentation
references/sdks/*.md
references/sdks/integrations/*.md
# Cookbook examples
references/cookbook/recipes/*.md
references/cookbook/applications/*.md
# Find specific topics
references/**/configuration.md
references/**/*python*.md
references/**/*deployment*.md
2. Search Content (use Grep tool)
# Search for concepts
pattern: "disposition" # Memory bank configuration
pattern: "graph retrieval" # Graph-based search
pattern: "helm install" # Kubernetes deployment
pattern: "document_id" # Document management
pattern: "HINDSIGHT_API_" # Environment variables
# Search in specific areas
path: references/developer/api/
pattern: "POST /v1" # Find API endpoints
path: references/cookbook/
pattern: "def |async def " # Find Python examples
3. Read Full Documentation (use Read tool)
references/developer/api/retain.md
references/sdks/python.md
references/cookbook/recipes/per-user-memory.md
Key Concepts
- Memory Banks: Isolated memory stores (one per user/agent)
- Retain: Store memories (auto-extracts facts/entities/relationships)
- Recall: Retrieve memories (4 parallel strategies: semantic, BM25, graph, temporal)
- Reflect: Disposition-aware reasoning using memories
- document_id: Groups messages in a conversation (upsert on same ID)
- Dispositions: Skepticism, literalism, empathy traits (1-5) affecting reflect
- Mental Models: Consolidated knowledge synthesized from facts
Notes
- Code examples are inlined from working examples
- Configuration uses
HINDSIGHT_API_*environment variables - Database migrations run automatically on startup
- Multi-bank queries require client-side orchestration
- Use
document_idfor conversation evolution (same ID = upsert)
Auto-generated from hindsight-docs/docs/. Run ./scripts/generate-docs-skill.sh to update.
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