SKILLEMALL.ai

BF quality-launch

面向新产线/新工厂质量负责人,系统策划投产质量启动(目标、交付物、质量门、爬坡与KPI),区别于安全投产遏制,输出质量启动计划(MD+HTML 双版)。

ClawHub Agent Skills author: engicool v0.1.0 MIT-0 2 files body ≈ 704 tokens Open the sourceclawhub.ai analyzed 2 d ago

面向新产线/新工厂质量负责人,系统策划投产质量启动(目标、交付物、质量门、爬坡与KPI),区别于安全投产遏制,输出质量启动计划(MD+HTML 双版)。

As a process F 31/100 · Will not run — References files that are not bundled: scripts/build_report.py

ProcedureData and analyticsAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
83/100
safety, quality, tests
Safety 60%
100
Quality 40%
57
Run on models
none yet
Process rating
F
31/100
Will not run
References files that are not bundled: scripts/build_report.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

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. 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: 0. 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")
  • warning missing-ref reference to a missing file: scripts/build_report.py
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "slug"

Process rating: all ten parameters 31/100

Will not run. References files that are not bundled: scripts/build_report.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/build_report.py
  • 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
  • 40Consistency. Frontmatter name (quality-launch) differs from the folder (skill-quality-launch)
  • 100Steps. 38 steps
  • 100Execution cost. Instruction body is 704 tokens
  • 100Running it twice. No mutating operations
  • low 11 top-level sections: this looks like several domains in one skill

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 76: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 38 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 57.

External checks

ClawHub: clean
This skill is a quality-planning assistant with no executable code, hidden data access, credential handling, or persistence.
LLM: benign (high) · VirusTotal: · 16 Jul 2026