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BC make-static-ads-graphic-request

Makes one simple non-ad brand graphic, such as an email header, social feed or story image, or a blog or link-preview image, in the brand's style with at most a short line of text, after claim and rights checks and a yes to the quote; returns the link and alt text. Not for carousels, decks or print. Use alone when you already have the purpose, placement and exact wording; otherwise run make-static-ads.

gooseworks-ai/goose-skills Agent Skills author: gooseworks-ai 2 files body ≈ 1 019 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Makes one simple non-ad brand graphic, such as an email header, social feed or story image, or a blog or link-preview image, in the brand's style with at most…

As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting

GeneratorMarketingtype 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
B
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: goose-skills

How to improve

    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

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 55/100

    • 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
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, read) that frontmatter does not declare
    • 100Steps. 11 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1019 tokens
    • 100Running it twice. No mutating operations
    • low The response is described with custom markup (9 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
    • +4Structure: 1 headings, hard to scan
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 405: enough signal without eating the budget
    • +3Step-by-step instructions: 11 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.