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BC marketing-assistant

市场营销助手（Marketing Assistant）。协助完成营销选题策划、推广海报文案生成、公众号文章起草、短视频口播脚本编写、营销活动方案策划、多平台内容发布包生成以及运营数据复盘。本工具由 @afeicn 提供支持。

ClawHub Agent Skills author: afeicn v0.1.0 MIT-0 16 files body ≈ 551 tokens Open the sourceclawhub.ai↗ analyzed 28 h ago

市场营销助手（Marketing Assistant）。协助完成营销选题策划、推广海报文案生成、公众号文章起草、短视频口播脚本编写、营销活动方案策划、多平台内容发布包生成以及运营数据复盘。本工具由 @afeicn 提供支持。

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

Proceduretype 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
81/100
safety, quality, tests
Safety 60%
89
Quality 40%
69
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

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 · 11

✓ No critical or high findings

Medium and low: 11
  • low Secrets in code secret-high-entropy-token employee.yaml:58
    High-entropy token-like string (may be an id, hash or a credential)
    - M06_…ack
  • low Secrets in code secret-high-entropy-token employee.yaml:65
    High-entropy token-like string (may be an id, hash or a credential)
    - M06_…ack
  • low Secrets in code secret-high-entropy-token employee.yaml:99
    High-entropy token-like string (may be an id, hash or a credential)
    - M06_…ack
  • low Secrets in code secret-high-entropy-token README.md:18
    High-entropy token-like string (may be an id, hash or a credential)
    | 活动策划 | 活动策划员 | 生成活动目标、流程、物料、节奏、分工和预算提示。 | M05_…ate, M06_…ack |
  • low Secrets in code secret-high-entropy-token README.md:19
    High-entropy token-like string (may be an id, hash or a credential)
    | 发布包生成 | 新媒体运营员 | 生成公众号、朋友圈、视频号等平台发布文案和标签。 | M06_…ack, M02_…ate |
  • low Secrets in code secret-high-entropy-token README.md:31
    High-entropy token-like string (may be an id, hash or a credential)
    | M06_…ack | 多平台发布包生成 | 按平台生成标题、正文、标签、封面建议、发布时间和差异化口径。 | publish_pack, platform_variants, tag_list, schedule_suggestion |
  • low Secrets in code secret-high-entropy-token skills/marketing_skills.yaml:81
    High-entropy token-like string (may be an id, hash or a credential)
    - id: M06_…ack
  • low Secrets in code secret-high-entropy-token workflows.md:113
    High-entropy token-like string (may be an id, hash or a credential)
    主要调用：M05_…ate、M06_…ack。
  • low Secrets in code secret-high-entropy-token workflows.md:122
    High-entropy token-like string (may be an id, hash or a credential)
    -> 调用 M05_…ate + M06_…ack
  • low Secrets in code secret-high-entropy-token workflows.md:139
    High-entropy token-like string (may be an id, hash or a credential)
    主要调用：M06_…ack、M02_…ate。
  • low Secrets in code secret-high-entropy-token workflows.md:148
    High-entropy token-like string (may be an id, hash or a credential)
    -> 调用 M06_…ack + M02_…ate

Files scanned: 16. 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. 27 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 551 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)
  • +3Description length 112: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 27 items
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: clean
This appears to be a coherent marketing-assistant skill whose logging and archival behavior is disclosed as part of the workflow, with privacy considerations users should review.
LLM: benign (medium) · VirusTotal: · 28 May 2026