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CC create-chatgpt-mockup

Render pixel-accurate ChatGPT mobile (iOS) screen mockups in light mode from a thread JSON. Supports user text bubbles, user image attachments, assistant markdown prose, citation chips, the OpenAI spiral logo, the Apps-SDK GPT chip in the composer, and three header styles (model-tag, plain title, "Get Plus"). Fixed 9:16 viewport. Outputs HTML + PNG.

athina-ai/goose-skills Agent Skills author: athina-ai 18 files · 5 scripts body ≈ 3 664 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Render pixel-accurate ChatGPT mobile (iOS) screen mockups in light mode from a thread JSON.

As a process C 57/100 · Has gaps — References files that are not bundled: templates/chat.css, examples/*.json, examples/assets/

GeneratorPlaywrightDesignAI 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%
100
Quality 40%
61
Run on models
none yet
Process rating
C
57/100
Has gaps
References files that are not bundled: templates/chat.css, examples/*.json, examples/assets/
Tools and files w 18
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: create-chatgpt-mockup (gooseworks-ai/goose-skills)

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: 13. 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: templates/chat.css
  • warning missing-ref reference to a missing file: examples/*.json
  • warning missing-ref reference to a missing file: examples/assets/
  • warning missing-ref reference to a missing file: examples/assets/sunscreen-sky.svg
  • note frontmatter-key unknown frontmatter key "status"
  • note frontmatter-key unknown frontmatter key "superseded_by"

Process rating: all ten parameters 57/100

Will not run. References files that are not bundled: templates/chat.css, examples/*.json, examples/assets/
  • 0Tools and files. 4 referenced file(s) missing: templates/chat.css, examples/*.json, examples/assets/
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 14 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 50 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3664 tokens
  • low 12 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (6 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 351: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 50 items
  • +3Output format is stated explicitly
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.