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BD a-stock-monitor

A股量化监控系统 - 7维度市场情绪评分、智能选股引擎（短线5策略+中长线7策略）、实时价格监控、涨跌幅排行榜。支持全市场5000+股票数据采集与分析，多指标共振评分，精确买卖点计算，动态止损止盈。每日自动推荐短线3-5只、中长线5-10只优质股票。包含Web界面、自动化Cron任务、历史数据回溯。适用于A股量化交易、技术分析、选股决策。

ClawHub Agent Skills author: xuchl2002 v1.0.0 28 files body ≈ 1 416 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

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
99
Quality 40%
70
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

The same skill appears in 1 more place: ClawHub

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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Dangerous commands cmd-background-process references/FINAL_SUMMARY.md:147
    Starts a background / autostarted process
    nohup python3 web_app.py > web_app.log 2>&1 &

Files scanned: 28. 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 "contact"

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-monitor) differs from the folder (a-stock-monitor-1-1-2)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 80 steps
  • 100Execution cost. Instruction body is 1416 tokens
  • 100Running it twice. No mutating operations
  • low 14 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
  • -2localhost URLs: will not work for another user
  • -32 of 14 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 170: enough signal without eating the budget
  • +4Structure: 42 headings
  • +3Step-by-step instructions: 80 items
  • +4Has examples (12 code blocks)
  • +4Reference files are cited in the instructions (1 of 9)

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

External checks

ClawHub: suspicious
The skill is a plausible stock-monitoring tool, but its web app ships with unsafe default access settings that users should review before installing.
LLM: suspicious (high) · VirusTotal: · 29 May 2026