ctx — Skill, Agent, MCP & Harness Recommendations

ctx watches what you are building, walks a 102,720-node graph, and recommends a small, top-scored bundle of skills, agents, and MCP servers for the current task. If you use your own local/API model instead of Claude Code, ctx has a separate harness setup flow: tell it the model and goal, review the recommended harness, then install with dry-run/update/uninstall controls.

Current shipped snapshot:

• 91,450 skills with hydrated installable SKILL.md bodies.
• 467 agents, 10,787 MCP servers, and 16 harnesses.
• 2.9M graph edges across semantic similarity, tags, slug tokens, source overlap, direct links, quality, usage, type affinity, and graph structure.
• 89,465 hydrated SKILL.md bodies in the shipped LLM-wiki; long entries are converted through the micro-skill gate instead of loading raw long prompts.
• Entity updates for skills, agents, MCPs, and harnesses print benefits/risks and skip replacement unless you explicitly approve the update.

Why it exists

• Discovery — with 91K+ skill nodes, 460+ agents, 10K+ MCP servers, and 16 harnesses, you can't possibly know which exist or which apply to your current work.
• Context budget — loading everything wastes tokens and degrades quality. You need the right 10–15 per session.
• Skill rot — skills you installed months ago and never used are cluttering context. Stale ones should be flagged automatically.

Install

pip install claude-ctx
ctx-init                    # terminal wizard: hooks, graph, model, harness goal
ctx-init --graph --hooks --model-mode skip  # fast runtime graph + Claude Code hooks
ctx-init --graph --graph-install-mode full  # expand the full markdown wiki locally
ctx-init --wizard           # force the same wizard from scripts/tests
ctx-init --model-mode custom --model openai/gpt-5.5 --goal "build a CAD agent"

Optional extras: pip install "claude-ctx[embeddings]" for the semantic backend, pip install "claude-ctx[harness]" for local/API model harness runs, pip install "claude-ctx[dev]" for the test toolchain.

Pre-built knowledge graph

Graph-backed recommendations need the pre-built graph. By default, ctx-init --graph installs the fast runtime artifact: graph/wiki-graph-runtime.tar.gz in source checkouts, or the matching GitHub release asset from pip installs. It contains graphify-out/*, the shipped skill index needed for recommendations, and the 16 harness pages needed by ctx-harness-install:

ctx-init --graph

The full LLM-wiki artifact remains available for local browsing, Obsidian, and expanded markdown pages:

ctx-init --graph --graph-install-mode full

The full wiki-graph.tar.gz includes the shipped skill index, 91,450 skill entity pages under entities/skills/, 89,465 hydrated installable SKILL.md files under converted/, and 16 harness pages under entities/harnesses/.

Windows: PowerShell's built-in tar.exe does not support --force-local; use tar -xzf graph\wiki-graph.tar.gz -C "$env:USERPROFILE\.claude\skill-wiki". In Git Bash or MSYS, use --force-local only when your -C target is a drive-letter path such as C:/Users/....

Use

After ctx-init --hooks or the wizard hook step, ctx observes Claude Code's `PostT

... View full README on GitHub