BC code-test-check
根据本地 PRD 需求文档或功能测试用例(Excel/JSON)，分析用户指定的后端与前端源码，验证需求功能点/测试用例是否被代码实现，输出 Markdown 验证报告（含代码证据与实现状态矩阵）。
根据本地 PRD 需求文档或功能测试用例(Excel/JSON)，分析用户指定的后端与前端源码，验证需求功能点/测试用例是否被代码实现，输出 Markdown 验证报告（含代码证据与实现状态矩阵）。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
ProcedureData and analyticsSoftware developmenttype and topics are labelled automatically from the skill text
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: 0. 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. 51 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1311 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 99: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- -5TODO / placeholder text left in the skill
- -212 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 11 headings
- +3Step-by-step instructions: 51 items
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.
External checks
ClawHub: clean
This skill is a source-code review helper that reads user-selected project files and creates a Markdown verification report, with no evidence of hidden, destructive, or unrelated behavior.
LLM: benign (high) · VirusTotal: · 2 Jul 2026