BD figma-design-analyzer
分析Figma设计文件,提取设计系统数据(颜色、字体、间距、组件),导出截图,并与实际实现进行比对验证。使用JavaScript/Node.js实现,当用户需要处理Figma设计文件、提取设计规范、导出设计资源或验证设计实现时使用此技能。
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
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 contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 5
✓ No critical or high findings
Medium and low: 5
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medium Dangerous commands
cmd-shell-rcREADME.md:85Writes to a shell startup fileecho 'export FIGMA_ACCESS_TOKEN="your_token_here"' >> ~/.zshrc
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low Exfiltration
read-dotenvREADME.md:38Reads a .env filecp .env.example .env
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low Exfiltration
read-dotenvREADME.md:61Reads a .env filecp .env.example .env
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low Exfiltration
read-dotenvREADME.md:80Reads a .env filecp .env.example .env
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low Exfiltration
read-dotenvscripts/figma-cli.js:26Reads a .env file (quoted — discussed, not commanded)console.error(chalk.yellow('1. 使用.env文件: cp .env.example .env 并填写您的令牌'));quoted
Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 46/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (node) that frontmatter does not declare
- 100Steps. 19 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 282 tokens
- 100Running it twice. No mutating operations
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 119: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -41 reference files, but SKILL.md never points to them: the model will not open them
- +1No license
- +2Single-language instructions
- +4Structure: 11 headings
- +3Step-by-step instructions: 19 items
- +4Has examples (6 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.