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BD geo-prohibited-word-checker

GEO/SEO内容违禁词检测与智能替换。当用户需要检测文章中的违禁词、检查GEO/SEO内容合规性、或要求替换违禁词时使用此技能。支持检测广告法违禁词（绝对化用语）、夸大宣传词、违法内容词、误导性词汇等，并根据上下文智能生成保留原意的替换方案。触发词：检测违禁词、检查违禁词、违禁词替换、违禁词修改、违规词、GEO合规检查、SEO合规、文章合规、内容合规。

ClawHub Agent Skills author: lijian2017 v1.1.0 MIT-0 7 files body ≈ 663 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

GEO/SEO内容违禁词检测与智能替换。当用户需要检测文章中的违禁词、检查GEO/SEO内容合规性、或要求替换违禁词时使用此技能。支持检测广告法违禁词（绝对化用语）、夸大宣传词、违法内容词、误导性词汇等，并根据上下文智能生成保留原意的替换方案。触发词：检测违禁词、检查违禁词、违禁词替换、违禁词修改、违规词、GEO合规…

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureMarketingtype 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
88/100
safety, quality, tests
Safety 60%
94
Quality 40%
78
Run on models
none yet
Process rating
D
43/100
Unfinished process
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

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.

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 · 2

✓ No critical or high findings

Medium and low: 2
  • medium Exfiltration net-redirectable-api-key scripts/detect_words.py:252
    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
  • low Secrets in code secret-password-literal references/deploy_guide.md:90
    Hard-coded password / key literal (may be an example) (quoted — discussed, not commanded)
    curl "https://geo-word-checker.<你的子域名>.workers.dev/admin/balance?admin_token=你的ADMIN_TOKEN&api_key=gw-a…xyz"
    quoted

Files scanned: 7. 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 "agent_created"

Process rating: all ten parameters 43/100

  • 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. 1 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 26 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 663 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 178: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 26 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: suspicious
This skill performs content checking as advertised, but its bundled paid-license service, automatic file writes, and credential-bearing network calls need review before installation.
LLM: suspicious (high) · 10 Jul 2026