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BC ai-content-collector

AI及汽车行业信息扫描收集工具。从指定渠道搜索和收集AI/汽车行业最新动态，整理为结构化Excel表格。覆盖：研发、营销、制造运营、财经人力、AI基础设施、模型能力、智能体开发平台、AI安全。触发：(1)收集AI/汽车行业动态、新闻、资讯 (2)扫描行业信息 (3)整理资料到Excel (4)信息周报/日报

ClawHub Agent Skills author: rouclaw v1.10.1 MIT-0 3 files body ≈ 5 590 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 52/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
82/100
safety, quality, tests
Safety 60%
100
Quality 40%
55
Run on models
none yet
Process rating
C
52/100
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. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 5590 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "tools"

Process rating: all ten parameters 52/100

  • 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
  • 70Execution cost. Instruction body is 5590 tokens
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 71 steps
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. No mutating operations
  • 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
  • -234 emoji in the instructions: noise for the model
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +3Description length 154: enough signal without eating the budget
  • +4Structure: 56 headings
  • +3Step-by-step instructions: 71 items
  • +4Has examples (31 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 55.

External checks

ClawHub: clean
This skill is a public-news collection workflow that creates spreadsheet reports, with no evidence of hidden data access, persistence, exfiltration, or destructive behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026