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AD zeelin-search

使用智灵搜索进行数据查询。当用户说"使用智灵搜索"、"智灵搜索帮我查询"、"调用智灵搜索"、"用智灵搜索"、"智灵搜索查询"、"舆情数据"、"舆情"、"新闻报道"、"...评论"、"热点话题"、"动态"、"相关报道"、"最新趋势"等时使用此技能。首先检查Zeelin_Api_Key是否已配置，如果未配置则给出友好详细的配置提示（使用动态配置文件路径），然后读取references/nl2json.md进行自然语言转JSON，再读取references/zenlin_search_api.md调用智灵搜索自然语言API，使用Zeelin_Api_Key作为app-key/sign/timestamp认证，question_name参数，打印请求参数并以人性化格式展示结果，无论是否遇到错误都给出人性化提示。只检查和提示Zeelin_Api_Key，不检查也不提示Zeelin_Api_Url和Zeelin_Website_Url。

ClawHub Agent Skills author: urhd528 v1.0.0 7 files body ≈ 558 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 49/100 · 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
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
D
49/100
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

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
  • 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: 6. 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 49/100

  • 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
  • 40Consistency. Frontmatter name (zeelin-search) differs from the folder (zeelin-search-gsdata-es-bigdata)
  • 100Tools and files. No external tools needed
  • 100Steps. 74 steps
  • 100Execution cost. Instruction body is 558 tokens
  • 100Running it twice. No mutating operations
  • medium 3 test cases, all positive: not one "should refuse" or "should ask first"

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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +3Description length 418: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 74 items
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: suspicious
This appears to be a real Zeelin search skill, but it can send API keys and searches to a plain-HTTP endpoint and automatically save full results locally.
LLM: suspicious (high) · VirusTotal: · 29 May 2026