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BC crebee-social-media-gateway

CreBee 社交媒体网关。当用户需要管理社交媒体账号、发布内容（视频/图文/文章）、获取数据分析、访问粉丝画像、搜索话题/活动/音乐、或与抖音、B站、小红书、快手等 12 个平台交互时触发此技能。适用于 AI Agent 自动化管理中国社交媒体平台运营。 触发场景： - 发布内容到社交媒体平台 - 获取账号列表或账号信息 - 查询分析数据、数据概览、表现指标 - 访问粉丝/观众画像 - 搜索话题、标签、音乐、活动 - 管理抖音、B站、小红书、快手等平台的内容

ClawHub Agent Skills author: Scarlett_AI v1.0.1 MIT-0 15 files body ≈ 2 224 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

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

IntegrationAI and agentsInfrastructuretype 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%
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. 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 Secrets in code secret-high-entropy-token references/platforms/qiehao.md:145
    High-entropy token-like string (may be an id, hash or a credential)
    #### getS…urs

Files scanned: 15. 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 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. 6 mutating operations with no state check
  • 100Tools and files. No external tools needed
  • 100Steps. 27 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2224 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)
  • +3Output format is not stated: the model decides each time
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +3Description length 233: enough signal without eating the budget
  • +4Structure: 23 headings
  • +3Step-by-step instructions: 27 items
  • +4Has examples (15 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

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

External checks

ClawHub: suspicious
This is a real social-media automation skill that is purpose-aligned, but it gives an agent broad live publishing and account-data access without enough approval, scoping, or privacy guidance.
LLM: suspicious (high) · VirusTotal: · 29 May 2026