SKILLEMALL.ai
GitHub ↗ RU Sign in

CF 百度知道回答自动发布

在百度知道指定问题下，把本地准备好的回答文稿自动发布为回答。

ClawHub Agent Skills author: MasterDXD v1.1.0 MIT-0 80 files · 1 script body ≈ 775 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

在百度知道指定问题下，把本地准备好的回答文稿自动发布为回答。

As a process F 28/100 · Will not run — References files that are not bundled: scripts/jiangchang_skill_core/

ProcedureAI 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
C
71/100
safety, quality, tests
Safety 60%
85
Quality 40%
51
Run on models
none yet
Process rating
F
28/100
Will not run
References files that are not bundled: scripts/jiangchang_skill_core/
Tools and files w 18
0
Result and completion w 14
0
When it triggers w 12
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 3

✓ No critical or high findings

Medium and low: 3
  • medium Exfiltration net-redirectable-api-key scripts/service/answer_optimizer.py:135
    Helper sends the API key to a host configured by an environment variable — the key can be redirected to another server
    API key + configurable base URL from environment
  • medium Exfiltration net-redirectable-api-key scripts/service/entitlement_service.py:12
    Helper sends the API key to a host configured by an environment variable — the key can be redirected to another server
    API key + configurable base URL from environment
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: bash
    allowed-tools: bash

Files scanned: 79. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-short description under 40 chars: too little signal for triggering
  • 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/jiangchang_skill_core/

Process rating: all ten parameters 28/100

Will not run. References files that are not bundled: scripts/jiangchang_skill_core/
  • 0Tools and files. 1 referenced file(s) missing: scripts/jiangchang_skill_core/
  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 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
  • 40Consistency. Frontmatter name (百度知道回答自动发布) differs from the folder (publish-answer-baidu-know)
  • 100Steps. 31 steps
  • 100Execution cost. Instruction body is 775 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 30: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 31 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (1 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 51.

External checks

ClawHub: suspicious
The skill mainly matches its advertised Baidu Zhidao posting purpose, but it includes under-disclosed browser evasion, local profile fallback, and optional AI-generated posting paths that should be reviewed before installation.
LLM: suspicious (high) · 23 Jul 2026