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CD superreview-setup

Generates a project-tailored deep-review skill: domain-expert routing + scope discipline (blast radius, delivery, closeout) + mechanical gates + adversarial validation. Triggers: superreview, generate review skill, deep review skill, scope discipline review

kochetkov-ma/claude-brewcode Agent Skills author: kochetkov-ma 15 files · 4 scripts body ≈ 10 978 tokens Open the sourcegithub.com↗ analyzed 7 h ago

Generates a project-tailored deep-review skill: domain-expert routing + scope discipline (blast radius, delivery, closeout) + mechanical gates + adversarial…

As a process D 47/100 · Unfinished process — References files that are not bundled: references/SKILL.md.template, references/scope.md.template, references/scope.md

AnalyzerGitHubData and analyticsAI and agentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
80/100
safety, quality, tests
Safety 60%
100
Quality 40%
49
Run on models
none yet
Process rating
D
47/100
Unfinished process
References files that are not bundled: references/SKILL.md.template, references/scope.md.template, references/scope.md
Tools and files w 18
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

The same skill appears in 2 more places: claude-brewcode, claude-brewcode

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 10978 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: references/SKILL.md.template
  • warning missing-ref reference to a missing file: references/scope.md.template
  • warning missing-ref reference to a missing file: references/scope.md
  • warning missing-ref reference to a missing file: references/intent-guard.md.template
  • warning missing-ref reference to a missing file: references/{python,java-kotlin,typescript-react,go}.md

Process rating: all ten parameters 47/100

Will not run. References files that are not bundled: references/SKILL.md.template, references/scope.md.template, references/scope.md
  • 0Tools and files. 5 referenced file(s) missing: references/SKILL.md.template, references/scope.md.template, references/scope.md
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 43 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 40Execution cost. Instruction body is 10978 tokens: crowds the task out of the window
  • 100Steps. 39 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low The response is described with custom markup (40 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -216 emoji in the instructions: noise for the model
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 257: enough signal without eating the budget
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 39 items
  • +4Has examples (11 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 49.