SKILLEMALL.ai

BC auto-file-organizer-pro

自动文件整理器专业版面向高效文件治理场景,在免费版基础上扩展全功能自动化能力。解决文件整理的"规模与智能"痛点:大量重复文件占用空间需要清理、按扩展名分类不够准确需要内容感知、多个文件夹需要批量定时整理、团队需要共享分类规则、文件变更需要实时监控自动整理。Use。Use when 需要提升效率、自动化流程、批量处理、工作流优化时使用。不适用于需要人工创意判断的任务。

ClawHub Hermes author: 天轰穿 v1.0.0 MIT-0 3 files body ≈ 3 104 tokens Open the sourceclawhub.ai analyzed 3 d ago

自动文件整理器专业版面向高效文件治理场景,在免费版基础上扩展全功能自动化能力。解决文件整理的"规模与智能"痛点:大量重复文件占用空间需要清理、按扩展名分类不够准确需要内容感知、多个文件夹需要批量定时整理、团队需要共享分类规则、文件变更需要实时监控自动整理。Use。Use when…

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceInfrastructuretype 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
C
51/100
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

How to improve

  1. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Unexpected scalar at node end at line 5, column 100: …理、智能内容分类、批量定时整理与多目录批量处理.。自动文件整理器专业版面向高效文件治理场景,在免费版基础上扩展全功能自动化能力。解决文件整理的"规模与智能"" ^^^^^^^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning description-long-hermes description is 184 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • 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 "edition"
  • note frontmatter-key unknown frontmatter key "tools"

Process rating: all ten parameters 51/100

  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 54 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3104 tokens
  • low 18 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
  • +2Single-language instructions
  • +3Description length 184: enough signal without eating the budget
  • +4Structure: 47 headings
  • +3Step-by-step instructions: 54 items
  • +4Has examples (14 code blocks)
  • +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: suspicious
The skill is file-organization focused, but it gives broad automated authority over user files, background scheduling, and network notification/sync features without enough scoping or consent detail.
LLM: suspicious (high) · 28 Aug 2026