AC cursor-prd-generator
当用户说"帮我写 PRD"、"生成需求文档"、"我想做一个功能"、"Cursor 用的 spec"、"cursor-prd"、"生成 FEATURE_SPEC"等时，触发此 skill。接收用户1-3句话的小功能需求，引导澄清后生成结构化 PRD 文件（FEATURE_SPEC.md）和 Cursor 规则片段（.cursor/rules），专为粘贴进 Cursor 使用优化。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 53/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 15 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 520 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 6 example trigger phrases
- +3Description length 190: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 15 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.
External checks
ClawHub: clean
This is a PRD-generation skill whose file, network, and credential use are disclosed and aligned with creating prototypes and publishing PRDs, though users should watch its broad triggers and Chinese-only default output.
LLM: benign (medium) · VirusTotal: · 29 May 2026