SKILLEMALL.ai
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CF review-storybook

Review Paperclip stories for a feature or change using the Storybook catalog, production source, and existing browser tests. Report component, mock, interaction, and visual evidence separately.

The skillemall take

The skill promises to parse Paperclip stories from Storybook catalog, compare against production source and existing browser tests, and report component, mock, interaction, and visual evidence separately. In practice: two files, 784 body tokens, no scripts, no model runs. Code quality scores 52, process 28. Broken references flag missing files. No critical findings, but medium and low findings weren't assessed either—no sandbox execution happened. Safety score clean.

Needs a live Storybook and production access to work. Without sandbox proof or actual run examples, it's unclear what the skill extracts from stories or how it structures the report. Install only if you already have a Paperclip project and can debug on real data.

paperclipai/paperclip Agent Skills author: paperclipai MIT 2 files body ≈ 784 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Review Paperclip stories for a feature or change using the Storybook catalog, production source, and existing browser tests.

As a process F 28/100 · No process to follow — References files that are not bundled: ../../../maps/storybook-map/README.md, ../../../doc/DEVELOPING.md

AnalyzerData and analyticstype 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
81/100
safety, quality, tests
Safety 60%
100
Quality 40%
52
Run on models
none yet
Process rating
F
28/100
No process to follow
References files that are not bundled: ../../../maps/storybook-map/README.md, ../../../doc/DEVELOPING.md
Tools and files w 18
0
Steps w 15
0
Inputs and preconditions w 11
0
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.
  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: 2. 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")
  • warning missing-ref reference to a missing file: ../../../maps/storybook-map/README.md
  • warning missing-ref reference to a missing file: ../../../doc/DEVELOPING.md

Process rating: all ten parameters 28/100

Will not run. References files that are not bundled: ../../../maps/storybook-map/README.md, ../../../doc/DEVELOPING.md
  • 0Tools and files. 2 referenced file(s) missing: ../../../maps/storybook-map/README.md, ../../../doc/DEVELOPING.md
  • 0Steps. Prose only: no discrete steps
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 50Failures and branches. 0 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 784 tokens

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)
  • +4Structure: 1 headings, hard to scan
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 193: enough signal without eating the budget

Quality base 70; lint remarks subtract, signals add up to 100. Result: 52.