context-query

Queries archived decisions, failures, meetings, and git snapshots via semantic search.

3|1|Updated Feb 12, 2026

Search Tags:#knowledge management #context retrieval #semantic search #failure analysis #decision records #organizational memory

Ready to run

npx skills add https://github.com/standard-librarian/context-engineer --skill context-query

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: context-query
Source: https://github.com/standard-librarian/context-engineer/tree/main/skills/public/context-query
Command: npx skills add https://github.com/standard-librarian/context-engineer --skill context-query

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides AI agents with direct access to an organization's historical decisions, failures, and meeting outcomes, enabling more informed and context-aware actions.

Core Features & Use Cases

Semantic Search: Find relevant context using natural language queries.
Structured Data Access: Query Architectural Decision Records (ADRs), failure incidents, meeting notes, and git snapshots.
Use Case: Before implementing a new feature, an agent can use this skill to query for past decisions related to similar features or known issues to avoid repeating mistakes.

Quick Start

Use the context-query skill to find past decisions about database authentication.

Frequently Asked Questions about context-query

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I enable AI agents to query organizational knowledge for past decisions?▼

You can retrieve past decisions by using semantic search to query organizational knowledge, allowing your AI agents to find relevant context using natural language queries before implementing new features or making architectural choices.

Can I use semantic search to find historical failure incidents and meeting notes?▼

Yes, you can use semantic search to find historical failure incidents and meeting notes by querying organizational knowledge with natural language, enabling agents to retrieve relevant context and avoid repeating past mistakes.

How do I query Architectural Decision Records to avoid repeating past mistakes?▼

You can query Architectural Decision Records by accessing organizational knowledge through API endpoints, enabling agents to retrieve past decisions and known issues related to similar features to avoid repeating previous mistakes.

Does context retrieval support domain filtering and timeline queries for git snapshots?▼

Yes, context retrieval supports domain filtering, timeline queries, and graph traversal, enabling comprehensive access to git snapshots and historical data within the organizational knowledge base for AI agents.

What is the best way to access historical context for informed decision-making in AI agents?▼

The best way to access historical context is by integrating AI agents with API endpoints that provide semantic search, domain filtering, and graph traversal across ADRs, failures, and meetings for informed decision-making.

When do I need graph traversal for organizational memory retrieval?▼

You need graph traversal for organizational memory retrieval when mapping complex relationships between ADRs, failures, meetings, and git snapshots that semantic search or timeline queries alone cannot fully connect.