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Context-engineering audit (C1-C6) of skills and always-loaded rules. Use when trimming context bloat, auditing a plugin, or after a new Claude model ships.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/laurigates/claude-plugins --skill evaluate-context-engineering命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
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FinOps snapshot — org billing, workflow stats, cache usage. Use when you want a high-level view of CI spending or workflow health before diving deeper.
GitHub Actions billing, workflow efficiency, and waste analysis at org or repo level. Use when investigating CI/CD costs, wasted runs, or optimizing triggers.
正在显示 SKILL.md
基于 SOC 职业分类
| name | evaluate-context-engineering |
| description | Context-engineering audit (C1-C6) of skills and always-loaded rules. Use when trimming context bloat, auditing a plugin, or after a new Claude model ships. |
| args | [plugin | plugin/skill | --always-loaded] [--judge] |
| allowed-tools | Bash(python3 *), Bash(bash *), Read, Glob, Grep, Task, TodoWrite |
| argument-hint | git-plugin/git-commit --judge |
| model | opus |
| created | "2026-07-26T00:00:00.000Z" |
| modified | "2026-07-26T00:00:00.000Z" |
| reviewed | "2026-07-26T00:00:00.000Z" |
Audit a plugin, a single skill, or the always-loaded surface against the six context-engineering shifts Anthropic named for Claude 5 generation models, and report a C1–C6 card.
Two channels, deliberately kept apart:
| Channel | What it is | Cost |
|---|---|---|
| M — mechanical | check-context-engineering.py, deterministic proxies over the tree | free |
| J — judgment | an isolated agent scoring the frozen 1–5 rubric with quoted evidence | one subagent, --judge only |
Channel M ranks candidates; it cannot tell a load-bearing safety constraint from a restatement of a model default. Channel J makes that call. Never blend the two into one score — a mechanical proxy and a judgment answer different questions, and averaging them hides which one is driving a recommendation.
| Use this skill when... | Use alternative when... |
|---|---|
| Auditing whether a skill or rule is written for the old context rules | Checking structure/frontmatter/size lint → scripts/plugin-compliance-check.sh |
| A new Claude model shipped and the corpus needs re-reading | Measuring whether a skill still works → /evaluate:matrix |
Deciding what to cut from CLAUDE.md and .claude/rules/ | Actually migrating rules into skills → agent-patterns-plugin:meta-context-diet |
| You want ranked, evidence-backed cut candidates | Checking a skill reads clearly to a fresh agent → /evaluate:legibility |
| Dim | Shift | What the scanner measures |
|---|---|---|
| C1 | rules → judgment | Constraint markers per 1k chars, and how many sit next to a safety/irreversibility word |
| C2 | examples → interface design | Fenced-block share of the body; whether args enumerates its alternatives |
| C3 | upfront → progressive disclosure | Body size vs supporting files; disclosure levels (body → references → scripts) |
| C4 | repetition → single source of truth | 8-word shingle overlap between skills, rules, and CLAUDE.md |
| C5 | (the >80% claim) | Always-loaded chars: CLAUDE.md + rules with no paths: scope |
| C6 | simple specs → rich references | Multi-line shell blocks with no bundled script |
git rev-parse --show-toplevelfind . -maxdepth 2 -name plugin.json -path '*/.claude-plugin/*'find . -maxdepth 3 -path '*/.claude/rules/*.md'Parse $ARGUMENTS:
| Parameter | Default | Description |
|---|---|---|
plugin | whole repo | Scope to one plugin directory, e.g. git-plugin |
plugin/skill | — | Scope to one skill, e.g. git-plugin/skills/git-commit |
--always-loaded | off | Score only CLAUDE.md and the unscoped rules |
--judge | off | Also run Channel J on the target (one subagent per unit, max 3 units) |
--budget N | 100000 | Always-loaded char budget for the C5 ratchet |
Execute this audit:
python3 "${CLAUDE_SKILL_DIR}/scripts/check-context-engineering.py" --top 10
Add --target <plugin-or-skill-path> when the user scoped the run, and
--always-loaded-budget <N> when they passed --budget.
Read the KEY=VALUE block. STATUS=ERROR means only one thing: the
always-loaded surface is over budget. Every other finding is a WARN candidate,
not a verdict.
Render one row per dimension: the measured value, the count of flagged units,
and the top offender. State the totals for C5_ALWAYS_LOADED_EST_TOKENS and
SKILL_BODY_EST_TOKENS separately — they have different cost models and must
not be summed.
Rank findings by always-loaded cost × frequency, never by raw size. An
always-loaded rule costs on every turn; a skill body costs only when the skill
fires; a references/ file or script costs only when read or run. A large skill
body is a smaller problem than a medium-sized unscoped rule.
--judge only)For at most 3 flagged units, spawn one isolated subagent each:
Task subagent_type: general-purpose
prompt: Read the frozen rubric at docs/benchmarks/2026-07-context-engineering/rubric.md
and score <unit path> on C1-C6. Every score of 1, 2, 4 or 5 needs a
verbatim quote from the unit, copied exactly. If you cannot quote for a
score, score 3. Do not read the scanner's metrics.json.
Withhold Channel M's numbers from the judge — showing them anchors the judgment
to the proxy the rubric is supposed to check independently. Run judges
synchronously: the critique is the returned tool result
(agent-patterns-plugin:cold-read-gate).
For each recommendation give: the unit, the dimension, the token cost, the proposed change, and whether the evidence is proven (a judged quote) or proxy-only (Channel M alone).
Include at least one unit that earns its tokens and should not be cut. A report with no counter-finding has an agreement bias, not a clean corpus — the scanner flags constraint density, and some of the densest text is the safety-critical text that should stay.
Migrating rules into skills is agent-patterns-plugin:meta-context-diet's job —
it carries the per-candidate confirmation gate for lossy edits to always-loaded
files. This skill measures and recommends; it does not rewrite.
| Context | Command |
|---|---|
| Whole-repo card | python3 "${CLAUDE_SKILL_DIR}/scripts/check-context-engineering.py" |
| One plugin | ... --target git-plugin |
| Machine-readable | ... --json |
| CI ratchet (exit 1 over budget) | ... --strict |
| Full issue list | ... --max-issues 0 |
| Determinism check | ... --json | sha256sum (must be stable across runs) |
docs/benchmarks/2026-07-context-engineering/rubric.md — the frozen 1–5 anchors Channel J scores against.claude/rules/context-engineering.md — the standing house position and what it supersedes.claude/rules/skill-evaluation.md — the tiered cost model; ablation is the follow-up that turns a judgment into a measurementagent-patterns-plugin:meta-context-diet — migrates approved always-loaded candidates into skills