SKILLEMALL.ai

BC meta-skill-generator

AI 技能自动生成框架。用于自动扫描、注册、检索、生成、评估、测试、优化技能。 触发场景: 1. 用户要求创建"技能工厂" 2. 需要检索/生成/评估技能 3. 需要测试/优化技能代码 状态:核心功能已完成 ⚠️ 注意:首次使用需运行 `python scripts/embed_skill.py` 重建向量搜索库

ClawHub Agent Skills author: xjxjdnsnak-cell v1.0.0 MIT-0 35 files body ≈ 260 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
80/100
safety, quality, tests
Safety 60%
90
Quality 40%
65
Run on models
none yet
Process rating
C
53/100
Has gaps
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Obfuscation medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The files contain invisible characters, encoded commands or comments hidden from readers but visible to the model. What you read differs from what the agent sees.

For the author

Remove invisible characters (they usually sneak in through copy-paste) and encoded strings: no catalog will pass them. Instructions for the model must be readable by a human too.

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
  • medium Obfuscation uni-mixed-script-word skills_db.json:236
    Word mixing Latin and Cyrillic letters (homoglyph obfuscation) (2 occurrences)
    "description": "Skills 绠$悊鍔╂墜銆傚綋鐢ㄦ埛瑕佹眰鏌ョ湅skills鍒楄〃銆佹煡鐪媠kills鐘舵€併€佸垪鍑簊kills浣跨敤鏃惰Е鍙戙€傚姛鑳斤細(1) 鍒楀嚭鎵€鏈夊凡瀹夎鐨剆kills (2) 鏄剧ず姣忎釜skill鐨勮缁嗕俊鎭?(3) 鏌ョ湅skill鐨勪娇鐢ㄦ儏鍐垫椿璺冪姸鎬?…
  • medium Obfuscation uni-mixed-script-word vector_db.json:9502
    Word mixing Latin and Cyrillic letters (homoglyph obfuscation) (2 occurrences)
    "description": "Skills 绠$悊鍔╂墜銆傚綋鐢ㄦ埛瑕佹眰鏌ョ湅skills鍒楄〃銆佹煡鐪媠kills鐘舵€併€佸垪鍑簊kills浣跨敤鏃惰Е鍙戙€傚姛鑳斤細(1) 鍒楀嚭鎵€鏈夊凡瀹夎鐨剆kills (2) 鏄剧ず姣忎釜skill鐨勮缁嗕俊鎭?(3) 鏌ョ湅skill鐨勪娇鐢ㄦ儏鍐垫椿璺冪姸鎬?…

Files scanned: 34. 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 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 9 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 260 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
  • -43 reference files, but SKILL.md never points to them: the model will not open them
  • -311 of 17 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 160: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 9 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.

External checks

ClawHub: suspicious
This skill is a high-capability skill-generation and testing framework whose local code execution and external data flows are under-scoped and partly misleading.
LLM: suspicious (high) · VirusTotal: · 29 May 2026