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BF stock-research-team

Multi-role AI stock research team. When a user asks to analyze a stock (e.g. "分析贵州茅台", "analyze NVDA", "帮我看看AAPL"), this skill orchestrates technical, fundamental, macro, and sentiment analysts, followed by a bull-bear debate, trading strategy, risk review, and a director's final verdict with a composite score. Supports both A-shares and US stocks via MCP tools.

ClawHub Agent Skills author: charonling v1.0.0 MIT-0 10 files · 3 scripts body ≈ 840 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 35/100 · Will not run — References files that are not bundled: [股票代码]

AnalyzerAI and agentsInfrastructuretype 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
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: [股票代码]
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: 10. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: [股票代码]
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: [股票代码]
  • 0Tools and files. 1 referenced file(s) missing: [股票代码]
  • 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
  • 100Steps. 45 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 840 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -213 emoji in the instructions: noise for the model
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • -32 of 3 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +3Description length 364: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 45 items
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: clean
This is a coherent stock-analysis skill that installs a local market-data MCP server, with some install-time and privacy considerations but no artifact-backed malicious behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026