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AC find-api

🔍 Find API | 寻找可靠数据源 TRIGGERS: Use when agent needs to fetch external data, user mentions "reliable data source", "数据源", "API", or when web scraping is inefficient/inaccurate. A comprehensive guide to reliable data APIs across all domains. Helps agents find the best APIs instead of inefficient web scraping. Currently covers: Stock/Financial data, Weather, News, Maps, and more domains coming soon. 触发条件：Agent 需要获取外部数据、用户提到"可靠数据源"、"数据源"、"API"，或网页爬取效率低/不准确时。 跨领域可靠数据 API 的综合指南。 帮助 Agent 找到最佳 API，避免低效的网页爬取。 目前覆盖：股票/金融数据、天气、新闻、地图，更多领域持续完善中。

ClawHub Agent Skills author: yesilsin-netizen v0.0.2 MIT-0 3 files body ≈ 2 497 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 59/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI 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
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    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 · 0

    ✓ No critical or high findings

    Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 59/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 60Failures and branches. 2 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 18 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2497 tokens
    • 100Running it twice. Mutating operations check current state
    • low 13 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
    • -5TODO / placeholder text left in the skill
    • -2117 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +3Description length 543: enough signal without eating the budget
    • +4Structure: 19 headings
    • +3Step-by-step instructions: 18 items
    • +4Has examples (13 code blocks)

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

    External checks

    ClawHub: clean
    No malicious behavior is evidenced; the main caveat is that broad trigger words may make the skill activate more often than intended.
    LLM: benign (medium) · VirusTotal: · 29 May 2026