SKILLEMALL.ai
GitHub ↗ RU Sign in

AD zeelin-search-pro

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"、"...舆情数据"、"...舆情"、"...新闻报道"、"...热点话题"、"...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: Paulina Laitinen v1.0.10 MIT-0 8 files body ≈ 558 tokens Open the sourceclawhub.ai↗ analyzed 4 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
This is a copy of a skill from another catalog; the rating counts the canonical one: zeelin-search-pro (ClawHub)

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: 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")

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-pro) differs from the folder (zeelin-search)
  • 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 8 example trigger phrases
  • +3Description length 432: 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
The skill appears to be a real Zeelin search integration, but it asks for an API key while package identity metadata is inconsistent and it can send broad search requests to an external service and save full results locally.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026