AgentSkillsCN

comprehensive-research

当用户希望获得整合基本面、技术面与量化风险评估的全链路投资分析时使用,例如通过“full research”、“comprehensive analysis”、“analyze this stock deeply”或“build a complete investment view”等短语触发。

SKILL.md
--- frontmatter
name: comprehensive-research
description: Use when users ask for end-to-end investment analysis that combines fundamentals, technicals, and quantitative risk assessment, including trigger phrases like "full research", "comprehensive analysis", "analyze this stock deeply", or "build a complete investment view".

Comprehensive Research Skill

Workflow Checklist

Copy and track progress:

code
Comprehensive Research Progress:
- [ ] Step 1: Define research scope and decision horizon
- [ ] Step 2: Gather fundamental context with financial_research
- [ ] Step 3: Run technical structure analysis with quant_analysis
- [ ] Step 4: Run quantitative risk and performance diagnostics
- [ ] Step 5: Synthesize evidence into scenario-based thesis
- [ ] Step 6: Provide decision framework and monitoring plan

Step 1: Define Scope and Decision Horizon

Clarify target asset, benchmark, horizon (swing, medium-term, long-term), and risk tolerance.

Set output objective:

  • Investment thesis quality check
  • Entry/exit planning support
  • Portfolio role assessment

Step 2: Fundamental Context via financial_research

Use financial_research to gather:

  • Revenue, margins, cash flow quality
  • Balance sheet strength and leverage
  • Valuation context (multiples, growth vs price)
  • Filings/news catalysts and management commentary

Capture both strengths and fragilities:

  • Business moat durability
  • Earnings quality concerns
  • Macro sensitivity and sector cyclicality

If helpful, enrich with web_search and browser for latest public context and source triangulation.

Step 3: Technical Structure via quant_analysis

Use quant_analysis technical indicators to characterize market behavior:

  • Trend state: SMA/EMA structure and slope
  • Momentum: RSI/MACD confirmation or divergence
  • Volatility envelope: Bollinger and ATR dynamics
  • Support/resistance and breakout context

Translate indicators into regime labels:

  • Trend continuation
  • Mean reversion
  • Transition/chop

Step 4: Quantitative Risk Diagnostics

Use quant_analysis risk metrics for objective downside framing:

  • Historical volatility
  • Max drawdown and drawdown duration
  • Sharpe/Sortino for risk-adjusted profile
  • VaR or tail-risk proxy when appropriate

If portfolio context is provided, evaluate fit:

  • Correlation and diversification effect
  • Position sizing implications
  • Contribution to portfolio drawdown risk

Step 5: Synthesize into Scenario-Based Thesis

Build one integrated view from fundamental, technical, and risk evidence.

Provide at least three scenarios:

  1. Bull case with conditions that must hold
  2. Base case with most likely path
  3. Bear case with invalidation triggers

For each scenario include:

  • Key drivers
  • Observable confirmation signals
  • Risk controls or hedging ideas

Resolve contradictions explicitly (e.g., strong fundamentals but weak technicals).

Step 6: Decision Framework and Monitoring Plan

Produce actionable but non-deterministic guidance:

  • Watchlist conditions for entry
  • Conditions for reducing exposure
  • Conditions for thesis invalidation

Set monitoring cadence and metrics:

  • Fundamental checkpoints (earnings, revisions, balance sheet changes)
  • Technical checkpoints (trend break, volatility regime shift)
  • Risk checkpoints (drawdown threshold, correlation spike)

Close with confidence level, top uncertainties, and what new data would most likely change the conclusion.