SKILLEMALL.ai

AC iFinD-Finance-Data

iFinD (同花顺) financial data query - query stocks, funds, macroeconomics, industry economics, news and announcements. Supports smart stock/fund screening, financial data queries, announcement search, and macro/industry indicator search. Trigger: ifind, 同花顺, 股票查询, 基金查询, 宏观数据, 行业数据, 金融数据, 行情数据, 财务数据, 选股, 选基, 财经新闻, 上市公司公告, 热点事件, 股票基本面, 基金业绩, 经济指标, 金融资讯, financial data, stock query, fund query, macro data, market data

ClawHub Agent Skills author: InitialDD v1.0.1 MIT-0 5 files body ≈ 2 901 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 52/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
C
52/100
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: 5. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 52/100

    • 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
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 60Failures and branches. 2 branches
    • 100Steps. 62 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2901 tokens
    • 100Running it twice. No mutating operations
    • low 11 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 415: enough signal without eating the budget
    • +4Structure: 19 headings
    • +3Step-by-step instructions: 62 items
    • +4Has examples (6 code blocks)

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

    External checks

    ClawHub: suspicious
    This finance-data skill matches its stated purpose, but it disables HTTPS certificate checks while sending a user auth token to a remote API.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026