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BF quality-playbook

Run a complete quality engineering audit on any codebase. Derives behavioral requirements from the code, generates spec-traced functional tests, runs a three-pass code review with regression tests, executes a multi-model spec audit (Council of Three), and produces a consolidated bug report with TDD-verified patches. Finds the 35% of real defects that structural code review alone cannot catch. Works with any language. Trigger on 'quality playbook', 'spec audit', 'Council of Three', 'fitness-to-purpose', or 'coverage theater'.

github/awesome-copilot Agent Skills author: github MIT 31 files body ≈ 72 802 tokens Open the sourcegithub.com↗ analyzed 27 h ago

Run a complete quality engineering audit on any codebase.

As a process F 71/100 · Will not run — References files that are not bundled: references/filename.md, references/**

ProcedureSoftware developmentWriting and documentsData and analyticstype and topics are labelled automatically from the skill text
Runs in: GitHub Copilot / VS Code Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
98
Quality 40%
68
Run on models
none yet
Process rating
F
71/100
Will not run
References files that are not bundled: references/filename.md, references/**
Tools and files w 18
0
Execution cost w 6
10
Steps w 15
60
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  2. 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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Secrets in code secret-high-entropy-token quality_gate.py:2713
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    Test…ncy -- a future maintainer reading the
    quoted
  • low Risky intent intent-offensive-security references/exploration_patterns.md:288
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)
    - **Authorization scope inheritance:** An ACL check reads `request.user` (the raw authenticated principal). When invoked inside an impersonation context, the framework's canonical `request.effective_u
    quoted

Files scanned: 31. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 72802 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: references/filename.md
  • warning missing-ref reference to a missing file: references/**
  • note edit-residue the text marks something as outdated (lines 98, 133, 135, 521, 1025, 1035): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 71/100

Will not run. References files that are not bundled: references/filename.md, references/**
  • 0Tools and files. 2 referenced file(s) missing: references/filename.md, references/**
  • 10Execution cost. Instruction body is 72802 tokens: crowds the task out of the window
  • 60Steps. 417 steps, 17 vague phrases
  • 100Result and completion. Output format and completion criterion are stated
  • 100When it triggers. States when to use and when not to
  • 100Inputs and preconditions. Inputs and preconditions are listed
  • 100Failures and branches. 22 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 20 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (60 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)
  • -5TODO / placeholder text left in the skill
  • +2Single-language instructions
  • +3Description length 530: enough signal without eating the budget
  • +4Structure: 82 headings
  • +3Step-by-step instructions: 417 items
  • +3Output format is stated explicitly
  • +4Has examples (44 code blocks)
  • +4Reference files are cited in the instructions (12 of 16)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.