SKILLEMALL.ai
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AF skill-compass

Diagnose, fix, and prevent agent skill trigger failures. Use when a skill doesn't activate, when skills trigger incorrectly, when troubleshooting "skill not working" issues, when auditing skill descriptions for quality, when optimizing trigger accuracy, or when asked "why didn't my skill fire?". Also use proactively after installing new skills or when agent behavior seems to ignore available skills. Covers description optimization, YAML frontmatter validation, token budget analysis, conflict detection, and auto-remediation.

ClawHub Agent Skills author: Thomaszhou v1.1.0 MIT-0 5 files body ≈ 1 459 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Diagnose, fix, and prevent agent skill trigger failures.

As a process F 42/100 · Will not run — References files that are not bundled: scripts/analyze_failures.py

AnalyzerGitHubPowerPointAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
F
42/100
Will not run
References files that are not bundled: scripts/analyze_failures.py
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: ClawHub

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/analyze_failures.py

Process rating: all ten parameters 42/100

Will not run. References files that are not bundled: scripts/analyze_failures.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/analyze_failures.py
  • 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. 6 mutating operations with no state check
  • 40Consistency. Frontmatter name (skill-compass) differs from the folder (skill-compass-guardian)
  • 50Failures and branches. 0 branches, has a failure section
  • 85Steps. 38 steps, 1 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Execution cost. Instruction body is 1459 tokens
  • 100Progress reporting. Reports progress

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
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 529: enough signal without eating the budget
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 38 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

External checks

ClawHub: suspicious
This skill appears intended to audit and improve other skills, but its fix mode can persistently change skill files with weak scoping and safeguards.
LLM: suspicious (medium) · VirusTotal: · 14 Jun 2026