SKILLEMALL.ai

BD mx_stocks_screener

基于东方财富数据库,支持通过自然语言输入筛选A港美股、基金、债券等多种资产,支持多元指标筛选,含技术面、消息面、基本面及市场情绪等,可用于全球资产速筛、跨市场监控、投资组合构建、策略回测等场景。返回结果包含数据说明及 csv 文件。Natural language screener for investment assets across global markets, including A-shares, ETFs, bonds, HK and US stocks, and funds. It enables multi-dimensional filtering via technical, fundamental, sentiment and news indicators. Ideal for global asset selection, cross-market monitoring, portfolio construction and strategy backtesting.

ClawHub Agent Skills author: akiry09 v0.1.0 MIT-0 3 files body ≈ 776 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
D
49/100
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: 3. 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)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 49/100

  • 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 (mx_stocks_screener) differs from the folder (mx-mx-stocks-screener)
  • 100Tools and files. No external tools needed
  • 100Steps. 20 steps
  • 100Execution cost. Instruction body is 776 tokens
  • 100Running it twice. No mutating operations

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 454: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 20 items
  • +4Has examples (8 code blocks)
  • +3All 1 scripts are documented

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

External checks

ClawHub: clean
This finance-data skill uses an API key and external market-data service as expected for its stated purpose, with no evidence of hidden, destructive, or account-mutating behavior.
LLM: benign (medium) · VirusTotal: · 29 May 2026