H

hindsight-docs

by @vectorize-iov
4.5(20)

Provides comprehensive Hindsight documentation for AI agents, aiding in understanding and analyzing AI behavior, optimizing decision-making, and enhancing system transparency.

documentationproduct-knowledge-basetechnical-writingvector-databasesinformation-architectureGitHub
Installation
npx skills add https://github.com/vectorize-io/hindsight --skill hindsight-docs
compare_arrows

Before / After Comparison

1
Before

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.

After

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.

SKILL.md

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_id for conversation evolution (same ID = upsert)

Auto-generated from hindsight-docs/docs/. Run ./scripts/generate-docs-skill.sh to update.

User Reviews (0)

Write a Review

Effect
Usability
Docs
Compatibility

No reviews yet

Statistics

Installs7.3K
Rating4.5 / 5.0
Version
Updated2026年9月19日
Comparisons1

User Rating

4.5(20)
5
60%
4
40%
3
0%
2
0%
1
0%

Rate this Skill

0.0

Compatible Platforms

🔧Claude Code
🔧OpenClaw
🔧OpenCode
🔧Codex
🔧Gemini CLI
🔧GitHub Copilot
🔧Amp
🔧Kimi CLI

Timeline

Created2026年3月17日
Last Updated2026年9月19日
🎁 Agent Knowledge Cards
Survey