AD xiaoyaoclaw-workspace-auditor
OpenClaw workspace health auditor (read-only inspection): scans an agent workspace for directory-structure compliance, task/PROGRESS.md health, memory-log gaps, knowledge-base index orphans and junk files; outputs a severity-graded report (red/yellow/green) with fix suggestions via a zero-dependency Python script (scan_workspace.py, stdlib only). Use when user asks to audit/inspect/health-check the workspace (工作区体检/审计/健康 检查/看看工作区乱不乱/检查目录规范). 中文：OpenClaw 工作区体检工具（只读审计）。 扫描 agent 工作区健康度：目录结构合规（initializer 规范）、任务进度卡健康 （tracker PROGRESS.md）、记忆日志空窗（memory-distill 约定）、知识库索引 同步与孤儿文件（kb-retriever data_structure.md）、垃圾/临时文件；通过零依赖 Python 脚本（scan_workspace.py，纯标准库）输出分级报告（🔴/🟡/🟢）与修复 建议。只读不修：脚本永不修改/删除任何文件。
OpenClaw workspace health auditor (read-only inspection): scans an agent workspace for directory-structure compliance, task/PROGRESS.md health, memory-log…
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
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 (python) that frontmatter does not declare
- 100Steps. 11 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 460 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 703: enough signal without eating the budget
- +4Structure: 5 headings
- +3Step-by-step instructions: 11 items
- +4Has examples (1 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.