BD code-quality-analyzer
代码质量分析技能，用于分析代码仓库的周/月维度变更，生成交付报告并同步到代码质量分析系统数据库。触发场景：(1) 用户要求进行代码质量分析 (2) 生成周报/月报 (3) 统计代码变更 (4) 分析分支提交 (5) 同步分析数据到数据库。
As a process D 37/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
AnalyzerSoftware developmentInfrastructuretype 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.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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") - warning
body-longSKILL.md body ≈ 8682 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 37/100
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 12 mutating operations with no state check
- 40Consistency. Frontmatter name (code-quality-analyzer) differs from the folder (fightingdao-code-quality-analyzer)
- 40Execution cost. Instruction body is 8682 tokens: crowds the task out of the window
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 100Steps. 38 steps
- 100Progress reporting. Reports progress
- low 28 top-level sections: this looks like several domains in one skill
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
- -4Absolute local paths (C:\Users, /home/…): not portable
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +4Structure: 106 headings
- +3Step-by-step instructions: 38 items
- +4Has examples (55 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 53.
External checks
ClawHub: suspicious
This appears to be an internal code-quality reporting skill, but it can overwrite reporting data, delegate code review to another model, and reference notification channels without enough user control or disclosure.
LLM: suspicious (high) · VirusTotal: · 29 May 2026