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CB find-data

Find a dataset for a Data2Story blog. Accepts a topic, a URL, or a DIP-style category. Downloads + validates against 4 completeness gates before handing off to /data2story-pro. Local-first: searches Economist/Pudding/TidyTuesday clones before going online. Supports --validate-only to audit a folder you already have.

QinghongLin/data2story-skill Claude Code author: QinghongLin 11 files · 5 scripts body ≈ 3 108 tokens Open the sourcegithub.com↗ analyzed 16 h ago

Find a dataset for a Data2Story blog.

As a process B 70/100 · Nearly there — weak spots: result and completion, when it triggers

AnalyzerExcelGitHubGoogle DriveData and analyticsWriting and documentstype 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
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
B
70/100
Nearly there
Result and completion w 14
0
When it triggers w 12
20
Failures and branches w 10
65
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 11. 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")

Process rating: all ten parameters 70/100

  • 0Result and completion. Does not say what the result is
  • 20When it triggers. No condition that starts the skill
  • 65Failures and branches. 3 branches
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 52 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3108 tokens
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • low 10 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (18 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
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +3Description length 317: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 52 items
  • +4Has examples (8 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.