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vectorize-io/hindsight4.6k installs

hindsight-docs

Complete Hindsight documentation for AI agents. Use this to learn about Hindsight architecture, APIs, configuration, and best practices.

How do I install this agent skill?

npx skills add https://github.com/vectorize-io/hindsight --skill hindsight-docs
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    This skill is a technical documentation repository for Hindsight, an agent memory system. It contains architectural diagrams, API references, installation guides, and best practices. All external resources, including CLI installation scripts and software packages, are legitimate vendor resources belonging to the skill author (vectorize-io). No malicious behavior, prompt injection, or data exfiltration patterns were detected.

  • Socketpass

    No alerts

  • Snykwarn

    Risk: MEDIUM · 2 issues

  • Runlayerfail

    30/42 files flagged

  • ZeroLeakspass

    Score: 93/100 · 2 sections analyzed

What does this agent skill do?

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/
├── 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
└── 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

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/, hindsight-docs/src/pages/cookbook/, and hindsight-docs/docs-integrations/. Run ./scripts/generate-docs-skill.sh to update.

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/vectorize-io/hindsight/hindsight-docs">View hindsight-docs on skillZs</a>