What do I need to use Context Engineering Review?

A real assembled context; The failure or goal; What varies per request; The model and its context limit.

Is Context Engineering Review free to use?

Yes — run it free in the browser playground (no API key needed for the sponsored trial, or bring any provider key), or install it into Claude Code, Cursor, ChatGPT and more via npx pm-claude-skills. MIT-licensed and open source.

Context Engineering Review

Q: How do I know the Context Engineering Review output is good?

The skill verifies itself against its own quality checks: The review used at least one real assembled request, or explicitly flags it could not; Every verdict has a reason tied to the stated failure/goal, not generic advice; Cache-breaking dynamic content in the stable prefix is called out with its cost; The token budget sums under the model limit at p95 including output headroom.

🔵 Stable🕐 updated 2026-07-01 🔷 SkillSpec L3 pm-agentops

Review what an LLM feature or agent actually puts in its context window — and find what's bloating, missing, or fighting itself. Use when asked to review a system prompt and context assembly, cut token usage without losing quality, debug an agent that ignores instructions, or audit how retrieval results, history, and tool definitions are packed into the window. Produces a context inventory with a keep/cut/restructure verdict per component, ordering and caching fixes, and a token budget. For wording-level prompt tuning use prompt-optimizer.

▶ Run it free — no key needed 📝 Grade your existing draft View SKILL.md ↗

What to give it

▸A real assembled context — an actual logged request (system prompt + messages + tools), not the template. If only the template exists, review that but flag that dynamic bloat is invisible

▸The failure or goal — ignoring instructions? too expensive? inconsistent? slow?

▸What varies per request — (retrieval, history, user data) vs. what is static

▸The model and its context limit — , and current typical request size

✅ The bar it holds itself to

Every skill in this library self-verifies — these are this skill's own quality checks, straight from its definition.

✓The review used at least one real assembled request, or explicitly flags it could not

✓Every verdict has a reason tied to the stated failure/goal, not generic advice

✓Cache-breaking dynamic content in the stable prefix is called out with its cost

✓The token budget sums under the model limit at p95 including output headroom

✓Recommended cuts come with a validation step before they ship

⚠️ What it refuses to do

Do not review the prompt template and call it a context review — the bloat lives in the dynamic parts

Do not recommend "shorten everything" — cutting the wrong 200 tokens costs more than keeping 2,000 idle ones

Do not leave contradictions in place because each section "is fine alone" — the window is read as one document

Do not treat more retrieval as more grounding — irrelevant chunks actively mislead

Do not propose structure the assembly code can't enforce — a budget without an enforcement point is a wish

Install

npx pm-claude-skills add --agent claude   # or codex · cursor · gemini · hermes
# or one-line MCP (every skill, any client):
claude mcp add pm-skills -- npx -y pm-claude-skills-mcp

Related skills

🔌 Embed this skill

Drop this on your blog, docs, or site — it renders a "Run this skill" card:

<div data-pm-skill="context-engineering-review"></div>
<script src="https://mohitagw15856.github.io/pm-claude-skills/embed.js" async></script>

💬 Discussion

Context Engineering Review is one of 551 open-source professional AI agent skills — all SkillSpec L3. Try them all in the browser · ⭐ Star on GitHub · Browse the full catalog