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小红书自动化发布技能。通过 Docker 容器中的 xiaohongshu-mcp 服务，实现登录、发布图文、搜索、互动等操作。 当用户提到发小红书、发笔记、发布内容、扫码登录小红书、小红书自动化、小红书发布时使用此技能。

ClawHub Agent Skills author: xiaohuozi v1.0.1 MIT-0 15 files body ≈ 684 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process F 33/100 · Will not run — References files that are not bundled: scripts/qrcode.png, scripts/images/, scripts/login_status.json

ReferenceDockerInfrastructureAI and agentstype 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
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
64
Run on models
none yet
Process rating
F
33/100
Will not run
References files that are not bundled: scripts/qrcode.png, scripts/images/, scripts/login_status.json
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: 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")
  • warning missing-ref reference to a missing file: scripts/qrcode.png
  • warning missing-ref reference to a missing file: scripts/images/
  • warning missing-ref reference to a missing file: scripts/login_status.json
  • warning missing-ref reference to a missing file: scripts/qrcode_result.json

Process rating: all ten parameters 33/100

Will not run. References files that are not bundled: scripts/qrcode.png, scripts/images/, scripts/login_status.json
  • 0Tools and files. 4 referenced file(s) missing: scripts/qrcode.png, scripts/images/, scripts/login_status.json
  • 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. 3 mutating operations with no state check
  • 100Steps. 20 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 684 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 111: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 20 items
  • +4Has examples (7 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 10 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: suspicious
This skill is a coherent Xiaohongshu automation tool, but it gives a third-party Docker service persistent ability to act on a live social account with weak scoping and no required confirmation steps.
LLM: suspicious (high) · VirusTotal: · 29 May 2026