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hindsight-docs — how to use hindsight-docs how to use hindsight-docs, hindsight-docs setup guide, hindsight-docs alternative, hindsight-docs vs biomimetic memory systems, hindsight-docs install, hindsight-docs documentation, hindsight-docs python sdk, hindsight-docs nodejs integration, what is hindsight-docs, hindsight-docs kubernetes deployment

v1.0.0
GitHub

About this Skill

Perfect for AI Agent Developers needing comprehensive documentation for biomimetic memory system integration, particularly those working with Hindsight and Python/Node.js/Rust SDKs. hindsight-docs is a technical documentation skill for Hindsight, a biomimetic memory system that enables AI agents to learn and recall information.

Features

Configure memory banks and dispositions for optimal performance
Set up the Hindsight API server using Docker, Kubernetes, or pip
Integrate with Python, Node.js, and Rust SDKs for seamless development
Understand retrieval strategies including semantic, BM25, graph, and temporal
Learn about retain, recall, and reflect operations for effective memory management

# Core Topics

vectorize-io vectorize-io
[0]
[0]
Updated: 3/6/2026

Quality Score

Top 5%
51
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add vectorize-io/hindsight

Agent Capability Analysis

The hindsight-docs MCP Server by vectorize-io is an open-source Categories.community integration for Claude and other AI agents, enabling seamless task automation and capability expansion. Optimized for how to use hindsight-docs, hindsight-docs setup guide, hindsight-docs alternative.

Ideal Agent Persona

Perfect for AI Agent Developers needing comprehensive documentation for biomimetic memory system integration, particularly those working with Hindsight and Python/Node.js/Rust SDKs.

Core Value

Empowers agents to master Hindsight's architecture and core concepts, including retain/recall/reflect operations, memory bank configuration, and retrieval strategies like semantic, BM25, graph, and temporal, using Docker, Kubernetes, or pip for setup.

Capabilities Granted for hindsight-docs MCP Server

Configuring Hindsight memory banks and dispositions for optimized performance
Integrating Hindsight with Python, Node.js, or Rust SDKs for seamless development
Implementing effective retrieval strategies using semantic, BM25, graph, or temporal methods

! Prerequisites & Limits

  • Requires understanding of biomimetic memory systems and Hindsight architecture
  • Limited to agents compatible with Python, Node.js, or Rust SDKs
  • Dependent on Docker, Kubernetes, or pip for Hindsight API server setup
Project
SKILL.md
3.2 KB
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1.2 KB
package.json
240 B
Ready
UTF-8

# Tags

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SKILL.md
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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
1# Core API operations 2references/developer/api/*.md 3 4# SDK documentation 5references/sdks/*.md 6references/sdks/integrations/*.md 7 8# Cookbook examples 9references/cookbook/recipes/*.md 10references/cookbook/applications/*.md 11 12# Find specific topics 13references/**/configuration.md 14references/**/*python*.md 15references/**/*deployment*.md

2. Search Content (use Grep tool)

bash
1# Search for concepts 2pattern: "disposition" # Memory bank configuration 3pattern: "graph retrieval" # Graph-based search 4pattern: "helm install" # Kubernetes deployment 5pattern: "document_id" # Document management 6pattern: "HINDSIGHT_API_" # Environment variables 7 8# Search in specific areas 9path: references/developer/api/ 10pattern: "POST /v1" # Find API endpoints 11 12path: references/cookbook/ 13pattern: "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.

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