AC westockdata
查询A股、港股、美股个股/指数/ETF的详细数据，包括：K线/分时、财务报表（三大报表多期查询，支持跨市场批量对比）、资金流向、技术指标、筹码分析、股东结构、分红除权、业绩预告、公司简况、ETF基金数据（详情/持仓/净值）；以及大盘指数、行业/板块行情、板块成份股、板块区间涨幅排行、指数成份股、热搜、新股日历、投资日历等市场数据。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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
- 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: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 53/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 4 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2128 tokens
- 100Running it twice. No mutating operations
- low 12 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
- -236 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 166: enough signal without eating the budget
- +4Structure: 24 headings
- +3Step-by-step instructions: 4 items
- +4Has examples (15 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.
External checks
ClawHub: clean
This skill is a coherent public stock-market data helper, with the main caveat that it runs a pinned third-party npm CLI at use time.
LLM: benign (medium) · VirusTotal: · 29 May 2026