SKILLEMALL.ai

AD a-stock

A股金融数据查询与分析助手。当用户询问任何与A股相关的问题时,使用此技能——包括:查询个股信息、实时行情、分时走势、龙虎榜、行业板块、盘口异动、市场总貌等。触发词包括但不限于:股票、A股、沪市、深市、行情、涨停、跌停、板块、龙虎榜、盘口异动、个股、股价、总市值、证券,或任何带有6位股票代码的查询(如 600519、000001)。即使用户没有明确说"查股票",只要问题涉及股市数据,都应使用此 Skill。【重要】所有接口调用必须使用 `npx tsx ~/.gemini/skills/a-stock-skill/scripts/api-client.ts`,严禁使用 curl。

ClawHub Agent Skills author: wwzzsl v0.1.1 MIT-0 4 files body ≈ 1 430 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
D
41/100
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

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
  • 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-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "env"
  • note frontmatter-key unknown frontmatter key "runtime"
  • note frontmatter-key unknown frontmatter key "network"

Process rating: all ten parameters 41/100

  • 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 (a-stock) differs from the folder (stock-skill-2)
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 100Steps. 58 steps
  • 100Execution cost. Instruction body is 1430 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
  • +2Single-language instructions
  • +3Description length 292: enough signal without eating the budget
  • +4Structure: 28 headings
  • +3Step-by-step instructions: 58 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 1 scripts are documented
  • +1License stated

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

External checks

ClawHub: clean
This is a disclosed A-share stock data helper that uses a local Node script and an API key to query its declared stock-data provider.
LLM: benign (high) · VirusTotal: · 29 May 2026