SKILLEMALL.ai
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BD stock-invest-master

股票投资分析技能。道法+大师+AI的三位分析框架，支持A股、港股、美股。适用场景：个股分析、公司估值、财报解读、行业研究、投资决策、基本面分析、技术面分析、风险评估、资金流向、13F机构持仓、南北向资金、买入卖出建议、投资大师视角（格雷厄姆/巴菲特/芒格/段永平/林奇/费雪/索罗斯/马克斯/达利欧/西蒙斯）、价值投资、成长股分析、价值股筛选、PE/PB/ROE估值、DCF估值、PEG估值、护城河分析、安全边际、财务健康检查、盈利质量分析、现金流分析等、分析师评级。触发关键词：股票、分析、估值、投资。

ClawHub Agent Skills author: mickshu v3.9.2 MIT-0 23 files · 1 script body ≈ 412 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process D 46/100 · 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
84/100
safety, quality, tests
Safety 60%
99
Quality 40%
62
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Dangerous commands cmd-background-process scripts/manage_server.sh:45
    Starts a background / autostarted process
    nohup python3 "${SKILL_DIR}/serve_reports.py" "${PORT}" > "${LOG_FILE}" 2>&1 &

Files scanned: 23. 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")

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 (web) that frontmatter does not declare
  • 100Steps. 24 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 412 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
  • +4No input/output examples
  • -415 reference files, but SKILL.md never points to them: the model will not open them
  • -34 of 4 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 252: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 24 items
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.

External checks

ClawHub: suspicious
The skill is a stock-analysis tool, but it can automatically start an unauthenticated report web server that listens on all network interfaces and serves saved investment reports from the user's home directory.
LLM: suspicious (high) · VirusTotal: · 2 Jun 2026