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CD data2story-pro

Use to turn a dataset into a verifiable multimedia blog (a data story / data-driven article / interactive dashboard from a dataset). Orchestrator for the Data Journalist Agent (Data2Story): a 7-team newsroom (14 agents) running detective → scout → analyst → imagineer → editor → copywriter → designer → interaction → hero → cinematographer → programmer → auditor → critic → inspector in sequence. Trigger when the user hands over a dataset (CSV/JSON/folder/path) and wants a published story, blog post, or interactive report built from it. Creates a versioned project folder per run.

QinghongLin/data2story-skill Claude Code author: QinghongLin 26 files · 2 scripts body ≈ 14 029 tokens Open the sourcegithub.com↗ analyzed 16 h ago

Use to turn a dataset into a verifiable multimedia blog (a data story / data-driven article / interactive dashboard from a dataset).

As a process D 43/100 · Unfinished process — References files that are not bundled: designer/references/tools.json, ../frontend-design-pro/

AnalyzerData and analyticsWriting and documentsAI 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
82/100
safety, quality, tests
Safety 60%
94
Quality 40%
65
Run on models
none yet
Process rating
D
43/100
Unfinished process
References files that are not bundled: designer/references/tools.json, ../frontend-design-pro/
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
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 · 2

✓ No critical or high findings

Medium and low: 2
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash(*)
    allowed-tools: Bash(*) Read Write Glob Grep Skill Agent WebSearch WebFetch
  • low Secrets in code secret-high-entropy-token package-lock.json:232
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…c4p+Q21c…1pl+NfxV…tyt/Fi7D16Q==",
    detector

Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 14029 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: designer/references/tools.json
  • warning missing-ref reference to a missing file: ../frontend-design-pro/

Process rating: all ten parameters 43/100

Will not run. References files that are not bundled: designer/references/tools.json, ../frontend-design-pro/
  • 0Tools and files. 2 referenced file(s) missing: designer/references/tools.json, ../frontend-design-pro/
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 40Execution cost. Instruction body is 14029 tokens: crowds the task out of the window
  • 50Failures and branches. 0 branches, has a failure section
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 50 steps
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 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 (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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 583: enough signal without eating the budget
  • +4Structure: 34 headings
  • +3Step-by-step instructions: 50 items
  • +4Has examples (6 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.