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tradingagents-analysis

AI Verified v0.6.1
Fluxly profile Facts only: domain, agents, trust score, runtime, permissions and network
Domain
AI
Compatible agents
  • Claude Code
  • Cursor
  • Cline
  • Codex
  • Windsurf
  • Gemini CLI
  • +20
Trust score
92 / 100 · audit passed
Author / version / license
@KylinMountain · v0.6.1 · no license declared
Token usage
Lean
Setup complexity
Guided setup
External API key
Not required
Operating systems
Unspecified (assume cross-platform)
Runtime requirements
No special requirements
Permissions
  • Read-only
  • Shell exec
  • Env read
  • Write / modify
Network behavior
External requests
Install commands
26 variants

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools，默认拥有全部工具权限。

Output preview tradingagents-analysis.preview 
---
name: tradingagents-analysis
description: >- 使用 TradingAgents API，让 15 名专业 AI 分析师对 A 股进行五阶段深度协作研判，输出结构化投资建议。 | 阶段 | 智能体 | 职责 | |------|---…
category: ai
runtime: no special runtime
---

# tradingagents-analysis output preview

## PART A: Task fit
- Use case: >- 使用 TradingAgents API，让 15 名专业 AI 分析师对 A 股进行五阶段深度协作研判，输出结构化投资建议。 | 阶段 | 智能体 | 职责 | |------|--------|------| | 1. 分析团队 | 市场/新闻/情绪/基本面/宏观/聪明钱 | 多维度原始数据解读 | | 2. 博弈裁判 | 博弈论管理者 | 主力与散户预期差分析 | makes outbound network calls. Works with Claude Code, Cursor, Cline and 23 more..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “🎯 快速上手 / 🤖 系统架构：五阶段 15 智能体 / 🤖 System Architecture: 5 Stages · 15 Agents” and do not present inference as author intent.

## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “>- 使用 TradingAgents API，让 15 名专业 AI 分析师对 A 股进行五阶段深度协作研判，输出结构化投资建议。 | 阶段 | 智能体 | 职责 | |------|--------|------| | 1. 分析团队 | 市场/新闻/情绪/基本面/宏观/聪明钱 | 多维度原始数据解读 | | 2. 博弈裁判 | 博弈论管理者 | 主力与散户预期差分析 | makes outbound network calls. Works with Claude Code, Cursor, Cline and 23 more.”.
- **02** When the source has headings, the agent prioritizes “🎯 快速上手 / 🤖 系统架构：五阶段 15 智能体 / 🤖 System Architecture: 5 Stages · 15 Agents” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, run shell commands, read environment variables, write/modify files; may access external network resources; usually needs no extra API key.

## Running Rules
- read files, run shell commands, read environment variables, write/modify files; may access external network resources; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options.
Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

  • Core job: >- 使用 TradingAgents API，让 15 名专业 AI 分析师对 A 股进行五阶段深度协作研判，输出结构化投资建议。 | 阶段 | 智能体 | 职责 | |------|--------|------| | 1. 分析团队 | 市场/新闻/…
  • Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
  • Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

  • Structure: The skill is organized around “🎯 快速上手”, “🤖 系统架构：五阶段 15 智能体”, “🤖 System Architecture: 5 Stages · 15 Agents”, “📋 适用场景”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
  • Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
  • Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

  • Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
  • Invocation: Name tradingagents-analysis directly; if the source includes slash commands, start with the command and then add task context.
  • Validation: Start small and check whether the result follows “🎯 快速上手 / 🤖 系统架构：五阶段 15 智能体 / 🤖 System Architecture: 5 Stages · 15 Agents” before expanding.

Boundaries And Review

  • Dependencies: It usually needs no extra API key, so start with a small validation task.
  • Permissions: Declared permissions include read / shell-exec / env-read / write; ask the agent to state file, command, and rollback boundaries before acting.
  • Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

Discussion

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