mcp-skillset: Instructions file for Claude Code

CLAUDE.md

mcp-skillset CLAUDE.md is an instructions file for Claude Code from bobmatnyc/mcp-skillset. It costs 917 tokens per session, scanned A, original, MIT.

Project instructions for coding agents working on mcp-skillset, a Python package and MCP server that finds and recommends skills for AI coding assistants.

In plain words
What is it for?
Use them when contributing to mcp-skillset: review and update Linear tickets, follow the project’s Python and MCP conventions, and keep related work linked to the correct project.
Why use it?
They explain the project’s Linear ticket workflow, required ticket references, technologies, and development context.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: mentions Claude Code.

This is bobmatnyc/mcp-skillset's own configuration. It tells Claude Code how to work on mcp-skillset itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything mcp-skillset configures →

Reuse

Borrowing it

Nothing to install: this file belongs to bobmatnyc/mcp-skillset. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/bobmatnyc/mcp-skillset/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/bobmatnyc/mcp-skillset

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

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README.md
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Your own site
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Your own site · 80×15
<a href="https://agentmods.dev/instructions/bobmatnyc/mcp-skillset/claude-md"><img src="https://agentmods.dev/badge/instructions/bobmatnyc/mcp-skillset/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 917 This file is loaded in full into every session.
When invoked 917 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00917 $0.00917
Opus 5 $0.00458 $0.00458
Sonnet 5 $0.00183 $0.00183
Haiku 4.5 $0.00092 $0.00092

Measured 10d ago against content hash b959c9016f34, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

mcp-skillset CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

CLAUDE.md · 128 lines

How it starts

The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Claude AI Assistant - Project Context

Linear Project

Project: MCP-SkillSet: Dynamic RAG Skills for Code Assistants URL: https://linear.app/1m-hyperdev/project/mcp-skillset-dynamic-rag-skills-for-code-assistants-0000af8da9b0/overview Team: 1M HyperDev

Workflow Guidelines

When working on this project:

  1. Review tickets from this Linear project before starting new work
  2. Assign all new tickets to this project (Project ID: 0000af8da9b0)
  3. Reference ticket IDs in commit messages (e.g., 1M-XXX: description)
  4. Update ticket status as work progresses
  5. Link related work (PRs, commits, documentation) to tickets

Ticket Management

  • Epic/Project ID: 0000af8da9b0
  • Team Key: 1M
  • Ticket Prefix: 1M-XXX

Quick Links

Project Information

Name: mcp-skillset Type: Python Package / MCP Server Purpose: Dynamic RAG-powered skill discovery and recommendation system for AI code assistants

Key Technologies

  • Python 3.11+
  • MCP (Model Context Protocol)
  • ChromaDB (vector storage)
  • NetworkX (knowledge graph)
  • sentence-transformers (embeddings)

Distribution Channels

Supported AI Agents

  • Claude Desktop
  • Claude Code (VS Code extension)
  • Auggie (Cursor)

Development Workflow

  1. Check Linear project for active tickets
  2. Create/assign tickets for new features or bugs
  3. Implement changes with ticket references
  4. Test thoroughly (pytest with coverage)
  5. Update documentation
  6. Create PR with ticket reference
  7. Update ticket status upon completion

Release Process

See docs/DEPLOY.md for complete release workflow.

Read the full file on GitHub · 128 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 128 lines · 917 tokens per session scan A b959c9016f34

Subscribe to this mod's changes

mcp-skillset CLAUDE.md is an instructions file published in the GitHub repository bobmatnyc/mcp-skillset (20 stars, last pushed 6mo ago), licensed MIT. It adds 917 tokens to every session, about $0.0046 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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