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BD toupiaoya-creator

投票鸭是易企秀旗下的在线投票制作工具，支持模板检索与投票活动创建。 当用户需要制作投票、发起评选、组织投票活动时使用此 Skill。 核心功能： 1. 检索投票模板——按关键词、颜色、热度筛选，返回模板列表与链接 2. 创建投票作品——支持文字投票、图片投票、视频投票，可设置多选/单选、时间范围 3. 素材上传——换取 COS 临时凭证并上传到腾讯云 COS（如 `material/` 前缀） 4. 素材列表——分页查询当前用户已上传的图片素材（`material list`） 5. 作品列表——分页查询工作台场景/作品（`project list`） 6. 投票数据——查询作品投票提交数据（`project vote-data`） 7. 访问趋势——查询作品访问趋势数据（`project view-data`） 8. 选项管理——读取作品全部选项（`get_choices`）、更新单个选项（`update_choices`）、新增选项（`add_choices`） 9. 分组管理——读取分组（`get_groups`）、新增分组（`add_group`）、修改分组名（`update_group`） 触发词：易企秀、制作投票、创建投票、发起投票、在线投票、投票模板、评选投票、微信投票、 活动投票、投票系统、投票链接、二维码投票、投票活动怎么弄、怎么发起投票、 投票工具、投票网站、免费投票、作品评选、摄影投票、美食投票、萌娃投票

ClawHub Agent Skills author: Ranger v1.0.3 MIT-0 21 files body ≈ 1 920 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

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

ProcedureInfrastructuretype 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%
94
Quality 40%
73
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

The same skill appears in 1 more place: ClawHub

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/toupiaoya/constants.py:17
    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 Exfiltration net-credential-use scripts/toupiaoya/constants.py:25
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
    os.environ.get("TOUPIAOYA_COS_TOKEN_API_BASE") or "https://emw-api.toupiaoya.com"
    vendor-host

Files scanned: 21. 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 "summary"
  • note frontmatter-key unknown frontmatter key "read_when"

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. 2 mutating operations with no state check
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 80 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1920 tokens
  • low 12 top-level sections: this looks like several domains in one skill

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 625: enough signal without eating the budget
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 80 items
  • +4Has examples (20 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: clean
This skill’s network calls, token storage, and upload behavior are disclosed and fit its purpose of managing Toupiaoya voting projects.
LLM: benign (high) · VirusTotal: · 29 May 2026