BC skill-consolidator
吸星大法 / Skill Consolidator：扫描并整理本地已安装的 AI Agent skills / rules / commands（WorkBuddy、Trae、Cursor、Claude Code、Windsurf、Cline、Continue、Roo Code、GitHub Copilot、OpenAI Codex 等），检测同名冲突、功能重叠、触发词冲突与版本差异，生成整理报告与分类索引。当用户输入 /吸星大法 或 /skill-consolidator、请求整理/清理/查看 skills（如"帮我整理 skill"、"skills 冲突了"、"organize my skills"），或在安装新 skill 之前评估冲突时自动调用。Scans and consolidates installed AI Agent skills, detects conflicts and overlaps, generates cleanup reports and categorized indexes.
吸星大法 / Skill Consolidator：扫描并整理本地已安装的 AI Agent skills / rules / commands（WorkBuddy、Trae、Cursor、Claude Code、Windsurf、Cline、Continue、Roo Code、GitHub…
As a process C 58/100 · Has gaps — 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 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
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Broad scope
meta-broad-allowed-toolsSKILL.md:1Broad tool permissions pre-approved: Bashallowed-tools: Bash Read Glob Grep Write Edit
Files scanned: 5. 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") - note
frontmatter-keyunknown frontmatter key "agent_created"
Process rating: all ten parameters 58/100
- 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
- 20When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 19 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 568 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
- -31 of 2 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +3Description length 463: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 19 items
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.