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claude-plugins / context-engineering

CLAUDE.md2 starsChanged 5 months agoMITView on GitHub

Agent Skills for Context Engineering — an open collection of 14 Agent Skills teaching context engineering principles for production AI agent systems. Skills are platform-agnostic (Claude Code, Cursor, GitHub Copilot, any Open Plugins-conformant tool). Context engineering is the discipline of curating everything that enters a model's context window (system prompts, tool definitions, retrieved documents, message history, tool outputs) to maximize signal within limited attention budget. No top-level build system. Individual example projects have their own tooling: When creating or editing…

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    Word for word · 1

    1. LiamClarke1/claude-skills★ 0100% same

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    None found.

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    None found.

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repositoryOne other file it gives its agents.

The file

We split this CLAUDE.md into the rules it gives an agent

5 rules. About 0 are common, 3 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    No top-level build system.

    line 24
  2. Distinctive:

    When creating or editing skills:

    line 56
  3. Distinctive:

    Update root README.md: when adding new skills

    line 65
  4. Very specific:

    Update marketplace/plugin manifests: when adding skills (.claude-plugin/marketplace.json, .plugin/plugin.json)

    line 66
  5. Very specific:

    All 14 skills are distributed as a single plugin (context-engineering) in the marketplace manifest.

    line 70

≈ “Common” is an estimate: at least 1 in 5 of the 26,980 CLAUDE.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
CLAUDE.md

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Project Overview

Agent Skills for Context Engineering — an open collection of 14 Agent Skills teaching context engineering principles for production AI agent systems. Skills are platform-agnostic (Claude Code, Cursor, GitHub Copilot, any Open Plugins-conformant tool).

Context engineering is the discipline of curating everything that enters a model's context window (system prompts, tool definitions, retrieved documents, message history, tool outputs) to maximize signal within limited attention budget.

Repository Structure

  • skills/ — 14 skill directories, each containing a SKILL.md with YAML frontmatter (name, description) and optional references/ and scripts/ subdirectories
  • examples/ — 5 complete demonstration projects (digital-brain-skill, llm-as-judge-skills, book-sft-pipeline, x-to-book-system, interleaved-thinking)
  • docs/ — Research materials and reference documentation
  • researcher/ — Research output examples
  • template/SKILL.md — Canonical skill template (use when creating new skills)
  • SKILL.md (root) — Collection-level metadata and skill map
  • .claude-plugin/marketplace.json — Claude Code marketplace manifest (5 bundled plugins)
  • .plugin/plugin.json — Open Plugins format manifest (v2.0.0)

Build & Test Commands

No top-level build system. Individual example projects have their own tooling:

examples/llm-as-judge-skills (TypeScript, Node >= 18)

cd examples/llm-as-judge-skills
npm install
npm run build        # tsc
npm test             # vitest (19 tests)
npm run lint         # eslint
npm run format       # prettier
npm run typecheck    # tsc --noEmit

examples/interleaved-thinking (Python >= 3.10)

cd examples/interleaved-thinking
pip install -e ".[dev]"
pytest               # pytest + pytest-asyncio
ruff check .         # linting (100 char line length)

examples/digital-brain-skill (Node.js)

cd examples/digital-brain-skill
npm run setup
npm run weekly-review
npm run content-ideas
npm run stale-contacts

Skill Authoring Rules

When creating or editing skills:

  1. SKILL.md must stay under 500 lines — move detailed content to references/ directory
  2. YAML frontmatter is required — must include name and description fields
  3. Folder naming: lowercase with hyphens (e.g., context-fundamentals)
  4. Write in third person — descriptions are injected into system prompts; inconsistent POV causes discovery issues
  5. Platform-agnostic — no vendor-locked examples or platform-specific tool names without abstraction
  6. Token-conscious — challenge each paragraph: "Does Claude really need this?" Assume advanced audience
  7. Include a Gotchas section — experience-derived failure modes are the highest-signal content in any skill
  8. Update root README.md when adding new skills
  9. Update marketplace/plugin manifests when adding skills (.claude-plugin/marketplace.json, .plugin/plugin.json)

Plugin Architecture

All 14 skills are distributed as a single plugin (context-engineering) in the marketplace manifest. This avoids cache duplication — Claude Code caches each plugin's source directory separately, so multiple plugins pointing to source: "./" would each cache a full copy of the repo.

Progressive disclosure pattern: only skill names/descriptions load at startup; full content loads on activation.

Key Design Principles

  • Context quality over quantity — attention scarcity and lost-in-middle phenomenon mean more context is not always better
  • Sub-agents isolate context — they exist to manage attention budget, not simulate org roles
  • Skills reference each other — use plain text skill names (not links) in Integration sections to avoid cross-directory reference issues
  • Examples use Python pseudocode — conceptual demonstrations that work across environments, not production-ready implementations

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