SKILLEMALL.ai

AD acceptance-rate-analysis

对承接率下降做阶段式归因分析。适用于“今天/本周承接率为什么下降”“分析承接率下降原因”“看一下承接率环比是否下降及原因”等场景。先定位异常切片,再逐层判断是一级切片结构迁移、资方总量明显减少或分布左移、资产维度异常,还是进一步闭环到敏感资方侧收缩。

ClawHub Agent Skills author: mzhou1982 v1.0.2 MIT-0 7 files body ≈ 1 843 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
D
41/100
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

The same skill appears in 2 more places: ClawHub, ClawHub

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: 7. 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")

Process rating: all ten parameters 41/100

  • 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
  • 40Consistency. Frontmatter name (acceptance-rate-analysis) differs from the folder (acceptance-rate-analysis-new-2)
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 100Steps. 109 steps
  • 100Execution cost. Instruction body is 1843 tokens
  • 100Running it twice. No mutating operations
  • low 10 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -33 of 4 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +3Description length 125: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 109 items
  • +4Has examples (6 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
This analytics skill matches its stated purpose, but it ships and silently uses powerful DataWorks credentials and can log sensitive query data, so it needs review before installation.
LLM: suspicious (high) · VirusTotal: · 29 May 2026