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BF gr-competitor

竞品深度扫描。批量抓取对手落地页（title/h1/intro/pricing）、定价页、博客 top 10、 变更历史（Wayback）。底层调 actionbook（并发 30 tab + 省 90% token）。 当用户说"分析对手"、"看看竞品在做啥"、"找对标"、"扫一下 top 10"时调用。

ClawHub Agent Skills author: Iris Wei v1.0.0 MIT-0 3 files body ≈ 726 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 40/100 · Will not run — References files that are not bundled: scripts/scan-serp.sh, scripts/pricing-diff.py

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
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
F
40/100
Will not run
References files that are not bundled: scripts/scan-serp.sh, scripts/pricing-diff.py
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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 text references files that are not there: add them or drop the references.
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: 2. 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 missing-ref reference to a missing file: scripts/scan-serp.sh
  • warning missing-ref reference to a missing file: scripts/pricing-diff.py
  • note frontmatter-key unknown frontmatter key "source"

Process rating: all ten parameters 40/100

Will not run. References files that are not bundled: scripts/scan-serp.sh, scripts/pricing-diff.py
  • 0Tools and files. 2 referenced file(s) missing: scripts/scan-serp.sh, scripts/pricing-diff.py
  • 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
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 24 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 726 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 154: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 24 items
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: clean
This skill openly provides competitor-research workflows that use Actionbook to scan websites, with practical privacy and compliance cautions but no evidence of hidden or malicious behavior.
LLM: benign (high) · VirusTotal: · 20 Jun 2026