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Yahoo Finance API integration for OpenClaw. Use when users ask for stock prices, company financials, historical data, dividends, or market data. Supports real-time quotes, financial statements, and market analysis.

ClawHub Agent Skills author: ClawMem.com v0.1.7 MIT-0 23 files body ≈ 1 020 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationInfrastructuretype 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%
99
Quality 40%
78
Run on models
none yet
Process rating
D
48/100
Unfinished process
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
This is a copy of a skill from another catalog; the rating counts the canonical one: yahooclaw (ClawHub)

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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Secrets in code secret-password-literal test-alpha.js:10
      Hard-coded password / key literal (may be an example) (test fixture / example file)
      apiKey: '9Z6P…DN3'
      fixture

    Files scanned: 22. 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 48/100

    • 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
    • 30Running it twice. 1 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 100Steps. 52 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1020 tokens
    • 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
    • -223 emoji in the instructions: noise for the model
    • -42 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +3Description length 214: enough signal without eating the budget
    • +4Structure: 30 headings
    • +3Step-by-step instructions: 52 items
    • +4Has examples (8 code blocks)

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

    External checks

    ClawHub: suspicious
    This appears to be a legitimate finance-data skill, but it needs review because it includes an exposed Alpha Vantage API key in test code and gives direct buy/sell recommendations without clear financial-advice warnings.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026