SKILLEMALL.ai

BC find-simplifications

Use for a periodic repo-wide sweep of qwen-code for accumulated excess surface — dead components and files, orphaned locale keys, exports nothing consumes, added-then-removed scaffolding — filing candidates on a tracking issue and landing only what a maintainer has said yes to. Repo-wide and evidence-first; every consumer is named before anything is deleted. Not for tidying a diff you just wrote (that is bundled `/simplify`) and not for defects (that is `/review`).

QwenLM/qwen-code Agent Skills author: QwenLM Apache-2.0 3 files body ≈ 11 063 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Use for a periodic repo-wide sweep of qwen-code for accumulated excess surface — dead components and files, orphaned locale keys, exports nothing consumes…

As a process C 53/100 · Has gaps — References files that are not bundled: scripts/copy_bundle_assets.js, scripts/prepare-package.js

AnalyzerGitHubSoftware developmentCommercetype and topics are labelled automatically from the skill text
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
53/100
Has gaps
References files that are not bundled: scripts/copy_bundle_assets.js, scripts/prepare-package.js
Tools and files w 18
0
Inputs and preconditions w 11
0
Running it twice w 4
30
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 · 0

✓ No critical or high findings

Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 11063 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: scripts/copy_bundle_assets.js
  • warning missing-ref reference to a missing file: scripts/prepare-package.js
  • note edit-residue the text marks something as outdated (lines 80, 198): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 53/100

Will not run. References files that are not bundled: scripts/copy_bundle_assets.js, scripts/prepare-package.js
  • 0Tools and files. 2 referenced file(s) missing: scripts/copy_bundle_assets.js, scripts/prepare-package.js
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 34 mutating operations with no state check
  • 40Execution cost. Instruction body is 11063 tokens: crowds the task out of the window
  • 50When it triggers. No condition that starts the skill
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 15 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

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
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 469: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 15 items
  • +3Output format is stated explicitly
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.