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A股板块资金流向扫描器。当用户询问板块资金热点、板块排名、资金流向、哪些板块在涨、热点扫描、板块强弱对比时触发。通过TDX通达信实时行情,对25个主题板块(半导体、AI算力、机器人、创新药、新能源车等)的个股进行量化评分,输出板块热度排名、个股详情和资金流向分类。支持扫描全部板块或指定板块,结果可导出为CSV。触发词:板块扫描、资金流向、热点板块、板块排名、资金热点、板块强弱。

ClawHub Agent Skills author: hunkguo v1.0.0 MIT-0 10 files body ≈ 964 tokens Open the sourceclawhub.ai analyzed 2 d ago

A股板块资金流向扫描器。当用户询问板块资金热点、板块排名、资金流向、哪些板块在涨、热点扫描、板块强弱对比时触发。通过TDX通达信实时行情,对25个主题板块(半导体、AI算力、机器人、创新药、新能源车等)的个股进行量化评分,输出板块热度排名、个股详情和资金流向分类。支持扫描全部板块或指定板块,结果可导出为CSV。触发词…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
68
Run on models
none yet
Process rating
D
46/100
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: 10. 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 "agent_created"

Process rating: all ten parameters 46/100

  • 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
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 18 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 964 tokens
  • 100Running it twice. No mutating operations
  • low 10 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
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -34 of 5 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 190: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 18 items
  • +4Has examples (7 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: clean
This skill is a disclosed A-share sector scanner that fetches public market data and optionally writes user-requested CSV reports, with no evidence of hidden data access, persistence, exfiltration, or destructive behavior.
LLM: benign (high) · VirusTotal: · 9 Jul 2026