archivist-retriever — archivist-retriever library-first approach archivist-retriever, osrs-cache, community, archivist-retriever library-first approach, ide skills, archivist-retriever for TanStack Router, archivist-retriever for PandaCSS, Claude Code, Cursor, Windsurf

v1.0.0
GitHub

About this Skill

Ideal for Technical Support Agents requiring efficient access to local documentation for libraries and tools like TanStack Router and PandaCSS. Archivist-Retriever is a technical query resolution skill that prioritizes local documentation over internal knowledge, ensuring accurate and efficient information retrieval.

Features

Checks ./reference-material/docs for information before relying on internal knowledge
Supports tasks involving libraries and tools like PandaCSS
Resolves direct questions about project tech stack components like TanStack Router
Prioritizes local documentation for efficient technical query resolution
Enables accurate information retrieval for technical concepts
Facilitates implementation of technical concepts within the project's tech stack

# Core Topics

KurzaCationer KurzaCationer
[0]
[0]
Updated: 3/8/2026

Agent Capability Analysis

The archivist-retriever skill by KurzaCationer is an open-source community AI agent skill for Claude Code and other IDE workflows, helping agents execute tasks with better context, repeatability, and domain-specific guidance. Optimized for archivist-retriever library-first approach, archivist-retriever for TanStack Router, archivist-retriever for PandaCSS.

Ideal Agent Persona

Ideal for Technical Support Agents requiring efficient access to local documentation for libraries and tools like TanStack Router and PandaCSS.

Core Value

Empowers agents to resolve technical queries by prioritizing local documentation over internal knowledge, ensuring accurate and efficient task resolution for libraries, tools, and technical concepts, and streamlining development processes with TanStack Router and PandaCSS.

Capabilities Granted for archivist-retriever

Resolving technical queries about TanStack Router implementation
Retrieving documentation for PandaCSS integration
Debugging issues within the project's tech stack using local references

! Prerequisites & Limits

  • Requires access to local documentation at ./reference-material/docs
  • Limited to technical queries and tasks involving libraries, tools, and technical concepts
Labs Demo

Browser Sandbox Environment

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Boot Container Sandbox

archivist-retriever

Install archivist-retriever, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
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Archivist Retriever

Prioritize local documentation over internal knowledge for every technical query.

Triggers

  • Any task involving libraries, tools, or technical concepts (e.g., "How do I use PandaCSS?", "Implement a TanStack Router").
  • Direct questions about how something works within the project's tech stack.

Core Mandates

  • Library First: You MUST check ./reference-material/docs for information before relying on your internal knowledge or performing external searches.
  • Exhaustive Search: Use glob and search_file_content to find relevant information in the local documentation library.
  • Contextual Application: Apply the found documentation precisely to the current task, adhering to the documented patterns and versions.

Workflow: Retrieval & Activation

  1. Identify Need: Recognize when a task involves a technology or concept likely documented in ./reference-material/docs.
  2. Search Library:
    • Use glob to find relevant files in ./reference-material/docs/.
    • Use search_file_content to find specific keywords or symbols within those files.
  3. Analyze & Inform:
    • Read the relevant documentation files.
    • If information is found, explicitly state: "Found relevant documentation in ./reference-material/docs/. Applying these patterns..."
  4. Apply Knowledge: Proceed with the task using the retrieved documentation as the primary source of truth.
  5. Fallback: If the information is not found or is insufficient, explicitly state: "I could not find sufficient information in the local library. Activating archivist-researcher for further investigation."

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is archivist-retriever?

Ideal for Technical Support Agents requiring efficient access to local documentation for libraries and tools like TanStack Router and PandaCSS. Archivist-Retriever is a technical query resolution skill that prioritizes local documentation over internal knowledge, ensuring accurate and efficient information retrieval.

How do I install archivist-retriever?

Run the command: npx killer-skills add KurzaCationer/osrs-cache/archivist-retriever. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for archivist-retriever?

Key use cases include: Resolving technical queries about TanStack Router implementation, Retrieving documentation for PandaCSS integration, Debugging issues within the project's tech stack using local references.

Which IDEs are compatible with archivist-retriever?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for archivist-retriever?

Requires access to local documentation at ./reference-material/docs. Limited to technical queries and tasks involving libraries, tools, and technical concepts.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add KurzaCationer/osrs-cache/archivist-retriever. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use archivist-retriever immediately in the current project.

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