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CC auditor

Audit a generated Data2Story blog for build correctness across ALL modalities by ACTUALLY RENDERING it in a real headless browser (when available) — catching blank/0-width charts, broken/oversized media, desktop+mobile overflow, and dead interactions that source inspection cannot see — then having vision agents review the screenshots, playtesting every interactive, and walking the flagship capability contract. Plus VIEW every image for a wrong/AI-faked subject. Fixes layout in place; sends content-correctness problems back to the owning role. Use at Stage 6 after the Programmer assembles index.html and before the Critic; re-runs each revision round. Triggers: a built index.html exists, or you need to confirm charts/media/interactions actually render.

QinghongLin/data2story-skill Claude Code author: QinghongLin 7 files · 2 scripts body ≈ 6 154 tokens Open the sourcegithub.com↗ analyzed 16 h ago

Audit a generated Data2Story blog for build correctness across ALL modalities by ACTUALLY RENDERING it in a real headless browser (when available) — catching…

As a process C 52/100 · Has gaps — References files that are not bundled: ../../frontend-design-pro/references/quality_rubric.json, ../../dataviz-craft/references/axis_label_polish.json, ../../dataviz-craft/references/encoding_craft.json

AnalyzerPlaywrightData 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
84/100
safety, quality, tests
Safety 60%
95
Quality 40%
68
Run on models
none yet
Process rating
C
52/100
Has gaps
References files that are not bundled: ../../frontend-design-pro/references/quality_rubric.json, ../../dataviz-craft/references/axis_label_polish.json, ../../dataviz-craft/references/encoding_craft.json
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash(*)
    allowed-tools: Bash(*) Read Write Edit Grep Glob Agent

Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6154 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: ../../frontend-design-pro/references/quality_rubric.json
  • warning missing-ref reference to a missing file: ../../dataviz-craft/references/axis_label_polish.json
  • warning missing-ref reference to a missing file: ../../dataviz-craft/references/encoding_craft.json
  • warning missing-ref reference to a missing file: ../../frontend-design-pro/references/pitfalls.json

Process rating: all ten parameters 52/100

Will not run. References files that are not bundled: ../../frontend-design-pro/references/quality_rubric.json, ../../dataviz-craft/references/axis_label_polish.json, ../../dataviz-craft/references/encoding_craft.json
  • 0Tools and files. 4 referenced file(s) missing: ../../frontend-design-pro/references/quality_rubric.json, ../../dataviz-craft/references/axis_label_polish.json, ../../dataviz-craft/references/encoding_craft.json
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 38 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 70Execution cost. Instruction body is 6154 tokens
  • 100Steps. 40 steps
  • 100Result and completion. Output format and completion criterion are stated
  • 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 11 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (7 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 760: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 40 items
  • +3Output format is stated explicitly
  • +4Has examples (3 code blocks)
  • +3All 2 scripts are documented

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