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BF logo-svg-generator

Generate multi-size SVG logos from natural-language product briefs, following Simple Icons design rules; runs an iterative generate → visual-check → optimize loop with a vision-capable LLM. Invoke when the user asks to design a logo, brand mark, app icon or product icon from a description.

ClawHub Agent Skills author: Samon Yu v0.1.0 MIT-0 9 files body ≈ 4 191 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Generate multi-size SVG logos from natural-language product briefs, following Simple Icons design rules; runs an iterative generate → visual-check → optimize…

As a process F 55/100 · Will not run — References files that are not bundled: scripts/render_previews.py, scripts/config.json, scripts/validate_svg.py

GeneratorDesigntype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
98
Quality 40%
74
Run on models
none yet
Process rating
F
55/100
Will not run
References files that are not bundled: scripts/render_previews.py, scripts/config.json, scripts/validate_svg.py
Tools and files w 18
0
Running it twice w 4
30
Result and completion w 14
40
the three weakest of ten parameters · all ten

How to improve

  1. 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
  • low Secrets in code secret-high-entropy-token references/motif-patterns.md:53
    High-entropy token-like string (may be an id, hash or a credential)
    M3 0h4v…H3Z
  • low Secrets in code secret-high-entropy-token references/motif-patterns.md:85
    High-entropy token-like string (may be an id, hash or a credential)
    M4 14h4…-4Z

Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/render_previews.py
  • warning missing-ref reference to a missing file: scripts/config.json
  • warning missing-ref reference to a missing file: scripts/validate_svg.py
  • warning missing-ref reference to a missing file: scripts/export_variants.py
  • warning missing-ref reference to a missing file: scripts/simplify_for_small.py
  • warning missing-ref reference to a missing file: scripts/config.json.cdn_url_templates
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 55/100

Will not run. References files that are not bundled: scripts/render_previews.py, scripts/config.json, scripts/validate_svg.py
  • 0Tools and files. 6 referenced file(s) missing: scripts/render_previews.py, scripts/config.json, scripts/validate_svg.py
  • 30Running it twice. 5 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 40Consistency. Frontmatter name (logo-svg-generator) differs from the folder (logo-svg-generator-skill)
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 4191 tokens
  • 85Steps. 49 steps, 1 vague phrases
  • 100Failures and branches. 3 branches, has a failure section
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • high The skill tells the model to perform an irreversible action with no human approval
  • low The response is described with custom markup (21 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
  • +2Single-language instructions
  • +3Description length 290: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 49 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: clean
This skill is a coherent logo-generation workflow that writes local design files and uses a vision-capable LLM for review, with no evidence of hidden or destructive behavior.
LLM: benign (high) · VirusTotal: · 15 Jul 2026