hindsight-docs
Complete Hindsight documentation for AI agents. Use this to learn about Hindsight architecture, APIs, configuration, and best practices.
Best use case
hindsight-docs is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Complete Hindsight documentation for AI agents. Use this to learn about Hindsight architecture, APIs, configuration, and best practices.
Teams using hindsight-docs should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/hindsight-docs/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How hindsight-docs Compares
| Feature / Agent | hindsight-docs | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Complete Hindsight documentation for AI agents. Use this to learn about Hindsight architecture, APIs, configuration, and best practices.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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)
```bash
# 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)
```bash
# 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_id` for conversation evolution (same ID = upsert)
---
**Auto-generated** from `hindsight-docs/docs/`. Run `./scripts/generate-docs-skill.sh` to update.Related Skills
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