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BD incident-commander

Incident Commander Skill

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 27 files body ≈ 3 849 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Incident Commander Skill

As a process D 42/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype 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
B
84/100
safety, quality, tests
Safety 60%
98
Quality 40%
62
Run on models
none yet
Process rating
D
42/100
Unfinished process
Result and completion w 14
0
When it triggers w 12
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Risky intent intent-offensive-security references/incident-response-framework.md:70
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    | **SEV1** | Total service outage or data breach affecting all users. Revenue loss exceeding $10K/hour. Security incident with active exfiltration. | Page IC + on-call within 5 min. All hands mobilize
  • low Risky intent intent-offensive-security SKILL.md:127
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    1. **Command and Control**

Files scanned: 27. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-short description under 40 chars: too little signal for triggering
  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 42/100

  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 2 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 60Steps. 156 steps, 4 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3849 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

  • +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 24: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -33 of 6 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 39 headings
  • +3Step-by-step instructions: 156 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (1 of 6)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.