SKILLEMALL.ai

AF xiapi-stock-sql-screener

基于SQL条件筛选A股股票,支持自定义条件组合、排序和数量限制。支持等于、大于、小于、区间范围、IN枚举、字段间比较等多种条件写法,支持AND/OR逻辑组合和括号嵌套。返回股票代码、名称、涨跌幅、CS强度、RPS相对强度、SCTR技术排名、所属板块、概念等详细数据。触发词:SQL选股、选股、股票筛选、技术筛选、量化筛选、自定义筛选、条件选股。适用场景:自定义多条件组合筛选、量化策略选股、技术指标组合筛选、复杂逻辑条件筛选。不适用场景:个股深度基本面分析、财报研究、估值建模。

ClawHub Agent Skills author: 三水清 v1.0.1 MIT-0 5 files body ≈ 1 901 tokens Open the sourceclawhub.ai analyzed 2 d ago

基于SQL条件筛选A股股票,支持自定义条件组合、排序和数量限制。支持等于、大于、小于、区间范围、IN枚举、字段间比较等多种条件写法,支持AND/OR逻辑组合和括号嵌套。返回股票代码、名称、涨跌幅、CS强度、RPS相对强度、SCTR技术排名、所属板块、概念等详细数据。触发词:SQL选股、选股、股票筛选、技术筛选、量化筛…

As a process F 40/100 · Will not run — References files that are not bundled: ../daxiapi/references/api-reference.md

ProcedureData and analyticsAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
Run on models
none yet
Process rating
F
40/100
Will not run
References files that are not bundled: ../daxiapi/references/api-reference.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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 missing-ref reference to a missing file: ../daxiapi/references/api-reference.md

Process rating: all ten parameters 40/100

Will not run. References files that are not bundled: ../daxiapi/references/api-reference.md
  • 0Tools and files. 1 referenced file(s) missing: ../daxiapi/references/api-reference.md
  • 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
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 87 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1901 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
  • -216 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 239: enough signal without eating the budget
  • +4Structure: 27 headings
  • +3Step-by-step instructions: 87 items
  • +4Has examples (7 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

External checks

ClawHub: clean
This is a disclosed stock-screening helper that queries a third-party DAXIAPI service and does not show hidden, destructive, or unrelated behavior.
LLM: benign (high) · VirusTotal: · 20 Jun 2026