DC xiaoyaoclaw-beautify-github-readme
OpenClaw skill that beautifies GitHub READMEs: redesign a repository homepage or create project-native visual assets — pure SVG heroes, section headers, diagrams, badges, GIF motion graphics, showcase modules, or hybrid SVG-composed PNG/WebP — with built-in render-level visual verification (scripts/visual_verify.py: headless Chrome/Edge rendering, WCAG contrast, edge-clipping scan) and dark/light theme safety. Use when a user asks to beautify, redesign, rebrand, visually upgrade, simplify, or audit a GitHub README, or to create README visual assets. If whole-README work versus asset-only work is unclear, ask which scope the user wants. For hero-like assets where pure SVG and generated raster material are both viable, explain the tradeoffs and confirm the implementation before creating the asset. Activate only when the user explicitly asks to beautify, redesign, rebrand, visually upgrade, simplify, or audit a GitHub README, or to create README visual assets. Do not activate for general questions, passive reading, or discussion of a README that does not request visual or audit work. Capabilities are split across the bundled scripts: scripts/visual_verify.py renders assets with headless Chrome/Edge and checks WCAG contrast and edge clipping, scripts/render_motion_gif.py turns named SVG layers into an animated GIF, scripts/audit_readme.py performs the static README/SVG audit, and scripts/svg_safety.py is the shared trust boundary that vets untrusted SVG input for both render paths. 中文：面向 OpenClaw 的 GitHub README 视觉美化技能：重新设计仓库主页，或创建项目原生 视觉素材——纯 SVG hero、章节标题、流程图、徽章、动效 GIF、SVG 混合构图等，内置渲染级 视觉验证（无头 Chrome/Edge 渲染、WCAG 对比度、边缘贴边检测）与深浅双主题安全。 能力由内置脚本分工实现：visual_verify.py 负责渲染级验证，render_motion_gif.py 负责 SVG 分层转 GIF，audit_readme.py 负责静态审计，svg_safety.py 是两条渲染路径共用的 不可信 SVG 信任边界。 仅当用户明确要求美化/重新设计/升级/简化/审查 GitHub 仓库主页或制作 README 视觉素材时 激活；对 README 的一般性提问、被动阅读或讨论不激活本技能。 触发词：README美化、美化README、GitHub主页设计、仓库主页改版、README hero、 README视觉、SVG首图、readme redesign、beautify readme、README 动效。
OpenClaw skill that beautifies GitHub READMEs: redesign a repository homepage or create project-native visual assets — pure SVG heroes, section headers…
As a process C 50/100 · Has gaps — References files that are not bundled: assets/readme/
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
How to improve
- Shorten the description to 1024 characters.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- The text references files that are not there: add them or drop the references.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
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medium Broad scope
meta-broad-allowed-toolsSKILL.md:1Broad tool permissions pre-approved: Bashallowed-tools: Read Write Edit Glob Grep Bash Env
Files scanned: 20. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1992 chars, limit 1024 - warning
body-longSKILL.md body ≈ 5272 tokens (recommended < 5000); move details to references/ - warning
missing-refreference to a missing file: assets/readme/ - note
description-budgetdescription takes 1992 of the ~15000-char shared budget for all skills
Process rating: all ten parameters 50/100
- 0Tools and files. 1 referenced file(s) missing: assets/readme/
- 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
- 30Running it twice. 24 mutating operations with no state check
- 70Execution cost. Instruction body is 5272 tokens
- 100Steps. 71 steps
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 5 branches, has a failure section
- 100Consistency. Name and required fields are in place
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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)
- +3Description length 1991: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +4Structure: 18 headings
- +3Step-by-step instructions: 71 items
- +4Has examples (9 code blocks)
- +4Reference files are cited in the instructions (7 of 9)
- +3All 4 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 45.