SKILLEMALL.ai

BC sdd

Scenario-Driven Detection — AI 자율 추론 기반 논리 결함 탐지/수정 프레임워크. 기능 에러(crash, 500)가 아닌 '논리적으로 비정상인 동작'을 찾아 자동 수정한다. 사용 시점: (1) URL을 주고 웹사이트 논리 테스트 요청, (2) 소스코드 프로젝트의 UI/API 논리 검증 요청, (3) '시나리오 테스트', 'SDD 돌려줘', '논리 결함 찾아줘' 등의 요청. 플랫폼 무관(웹/모바일/API).

ClawHub Agent Skills author: kimky1122 v1.0.0 MIT-0 4 files body ≈ 1 056 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerData and analyticsDesigntype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
69
Run on models
none yet
Process rating
C
56/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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: 4. 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 56/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 100Tools and files. No external tools needed
  • 100Steps. 71 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1056 tokens
  • 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)
  • +3Output format is not stated: the model decides each time
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • +2Single-language instructions
  • +3Description length 241: enough signal without eating the budget
  • +4Structure: 22 headings
  • +3Step-by-step instructions: 71 items
  • +4Has examples (6 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: suspicious
This is a legitimate testing skill, but it can broadly crawl authenticated apps, handle session credentials, write reports, and automatically change or commit code without enough user-control boundaries.
LLM: suspicious (high) · VirusTotal: · 29 May 2026