SKILLEMALL.ai

AC workspace-hygiene

Use this skill only when the user explicitly asks for a dry-run cleanup inventory, disk-space cleanup, deletion review, or recoverable archiving of generated workspace artifacts in a coding repo, such as caches, logs, test reports, screenshots, temporary databases, eval outputs, build outputs, or agent scratch files. Do not trigger just because the user says a repo is messy, asks for code review, asks for git status, wants README/docs cleaned up, requests memory cleanup, or asks for ordinary coding/testing/refactoring. If cleanup or archive/removal of workspace artifacts is not the main request, do not use this skill.

ClawHub Agent Skills author: hollis9087 v0.1.2 MIT-0 5 files body ≈ 946 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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 57/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 5 mutating operations with no state check
    • 40Consistency. Frontmatter name (workspace-hygiene) differs from the folder (agent-workspace-hygiene)
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 70Failures and branches. 6 branches
    • 100Steps. 29 steps
    • 100When it triggers. States when to use and when not to
    • 100Execution cost. Instruction body is 946 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • medium 3 test cases, all positive: not one "should refuse" or "should ask first"

    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
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 625: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 29 items
    • +4Has examples (2 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: clean
    The skill artifacts are workflow helpers for ClawHub and Convex tasks, with sensitive actions disclosed and guarded by user confirmation or existing CLI permissions.
    LLM: benign (high) · VirusTotal: · 31 May 2026