SKILLEMALL.ai

BD hekouwang-harness-check-skill

当用户要求检查、体检、回归、验收、解释或诊断会勇禾口王内容工作流 Harness,或维护、移植、打包、开源这个 Harness 检查器 Skill 时使用。统一调用仓库现有的 verify.sh、harness-check、Runtime Governance、Hook、Task Contract、Safety Gate、Episode、可观测性和失败台账检查,并分别报告本地、暂存区、CI 自动化结果与真实宿主烟测边界。

ClawHub Agent Skills author: 会勇禾口王的AI笔记 v1.0.0 MIT-0 5 files body ≈ 509 tokens Open the sourceclawhub.ai analyzed 3 d ago

当用户要求检查、体检、回归、验收、解释或诊断会勇禾口王内容工作流 Harness,或维护、移植、打包、开源这个 Harness 检查器 Skill 时使用。统一调用仓库现有的 verify.sh、harness-check、Runtime Governance、Hook、Task Contract、Safety…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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 · 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 description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "homepage"

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 (bash) that frontmatter does not declare
  • 100Steps. 20 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 509 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
  • +4No input/output examples
  • +2Single-language instructions
  • +3Description length 212: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 20 items
  • +4Reference files are cited in the instructions (1 of 1)
  • +1License stated

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

External checks

ClawHub: clean
This skill is a disclosed Harness verification helper that runs project-provided checks and clearly separates automated results from manual review boundaries.
LLM: benign (high) · VirusTotal: · 17 Aug 2026