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BC marketing-copy-knowledge

小黑老師 邱煜庭設計。Meta 廣告文案、Google 廣告文案、社群貼文：用 FABE x SPIN 產出更能轉換的廣告文案。支援 freemium/付費（X-Api-Key credits）。

ClawHub Agent Skills author: backtrue v1.0.3 2 files body ≈ 916 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 61/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationInfrastructuretype 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%
99
Quality 40%
68
Run on models
none yet
Process rating
C
61/100
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Obfuscation obf-hex-escape-chain SKILL.md:6
    Escaped/char-code string obfuscation (quoted — discussed, not commanded)
    metadata: {"author_name":"邱煜庭（小黑老師）","author_role":"Marketing instructor (Meta Ads / Google Ads / SEO / GA)","book_title":"《說進心坎裡》角色導向 FABE × SPIN 話術練習系統","book_url":"https://fabe.thinkwithblack.com/"
    quoted

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")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 61/100

  • 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. 1 mutating operations with no state check
  • 100Tools and files. No external tools needed
  • 100Steps. 23 steps
  • 100Failures and branches. 3 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 916 tokens

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)
  • +3Description length 98: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 23 items
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: clean
This skill is a disclosed marketing-copy helper that sends marketing prompts to one external service, with no hidden code, persistence, or local access found.
LLM: benign (high) · VirusTotal: benign · 28 May 2026