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hindsight-docs

hindsight-docs

github.com/vectorize-ioAgent workflows55.5k9.3k installsUpdated today
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About hindsight-docs

A documentation skill for AI agent developers working with Hindsight, covering its memory system, APIs, SDKs, and deployment. The references span memory operations, retrieval strategies, configuration, and performance troubleshooting.

Key features

  1. 01Look up retain, recall, and reflect operations
  2. 02Explore memory banks and disposition settings
  3. 03Find semantic, BM25, graph, and temporal retrieval docs
  4. 04Read Python, Node.js, and Rust SDK guides
  5. 05Consult deployment, API, and performance references

Use cases

  1. 01Learn Hindsight architecture and core concepts
  2. 02Configure memory banks and retrieval strategies
  3. 03Troubleshoot deployment or performance issues

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/vectorize-io/hindsight --skill hindsight-docs

After installing, type/hindsight-docsin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
best-practices.md
references/changelog/integrations/
ag2.md
agent-framework.md
agentcore.md
agno.md
ai-sdk.md
aider.md
autogen.md
chat.md
claude-agent-sdk.md
claude-code.md
cline.md
cloudflare-oauth-proxy.md
codex.md
coding-agents.md
composio.md
continue.md
copilot-cli.md
crewai.md
cursor-cli.md
cursor.md
devin-desktop.md
dify.md
eliza.md
eve.md
flowise.md
github-copilot.md
google-adk.md
haystack.md
hermes.md

Details

From the project README

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

Documentation Structure

All documentation is in references/ organized by category:

references/
├── best-practices.md # START HERE — missions, tags, formats, anti-patterns
├── faq.md            # Common questions and decisions
├── changelog/        # Release history and version changes (index.md + integrations/)
├── openapi.json      # Full OpenAPI spec — endpoint schemas, request/response models
├── developer/
│   ├── api/          # Core operations: retain, recall, reflect, memory banks
│   └── *.md          # Architecture, configuration, deployment, performance
└── sdks/
    ├── *.md          # Python, Node.js, CLI, embedded
    └── integrations/ # Framework and tool integrations

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

# 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/sdks/
pattern: "def |async def "    # Find Python examples
3. Read Full Documentation (use Read tool)
references/developer/api/retain.md
references/sdks/python.md
references/sdks/integrations/litellm.md

Start Here: Best Practices

Before reading API docs, read the best practices guide. It covers practical rules for missions, tags, content format, observation scopes, and anti-patterns — the fastest way to integrate correctly.

references/best-practices.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/ and hindsight-docs/docs-integrations/. Run ./scripts/generate-docs-skill.sh to update.

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