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Market analyze

Skill NatsuFox/A-Stockit/skills/astockit/market-analyze

A-Stockit —— 面向 Agent 框架的 A 股量化分析技能库,提供多样化市场操作,无需配置独立 trading bot

Install
npx -y skills add NatsuFox/A-Stockit --skill market-analyze

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Assess trend, regime, and risk state for one A-share symbol. Use when user wants current market interpretation from the normalized snapshot without action sizing, execution planning, or thesis narration.

SKILL.md

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Market Analyze

Assess scored market state for: $ARGUMENTS

Overview

  • Implementation status: code-backed
  • Local entry script: <bundle-root>/market-analyze/run.py
  • Primary purpose: turn normalized market data into a readable current-state interpretation
  • Research layer: descriptive analysis only
  • Workflow stage: stage 4 Signal and State Interpretation
  • Local executor guarantee: compute and return the current market snapshot summary, including score, bias, trend, regime, key levels, notes, and risk flags

Use When

  • The user wants current trend, regime, support, resistance, and risk-state interpretation.
  • The user wants descriptive market-state context before moving into decision-support, strategy-design, or technical-scan.
  • The user needs a bounded summary of the current snapshot rather than a thesis memo or full report.

Do Not Use When

  • The user wants a full report with decision and strategy sections. Use market-brief.
  • The user wants a direct trading action or quantity. Use decision-support.
  • The user wants technical-only pattern language or broader chart commentary beyond the runtime snapshot summary. Use technical-scan.
  • The user wants raw normalized data only. Use market-data.
  • The user wants broader catalyst, thesis, or variant-view analysis. Use analysis.

Inputs

  • Normal case: one stock symbol.
  • Optional --csv PATH: use a local CSV instead of the default market source.
  • Optional --start, --end, --source: constrain the data-loading path.
  • If symbol is omitted, the skill may reuse last_symbol from the same execution context.
  • Data note:
    • the local runtime derives its state from the normalized daily-bar frame
    • the user should not assume an intraday, benchmark-relative, or multi-factor attribution engine exists here

Execution

Step 1: Confirm the descriptive boundary

Use market-analyze for current-state interpretation only. It describes what the normalized snapshot currently looks like; it does not approve a position, design an execution plan, or validate a thesis.

Step 2: Run the local executor

python3 <bundle-root>/market-analyze/run.py <symbol> [--csv PATH]

Step 3: Deliver the snapshot honestly

The local output should be interpreted as a bounded state summary built from the enriched market frame. The agent should state:

  • the data source and date window
  • whether the symbol was explicit or reused from session context
  • that score and bias summarize current state heuristically
  • that the skill does not imply portfolio action, catalyst interpretation, or execution readiness

Output Contract

  • Minimum local executor output: human-readable text beginning with 市场分析.
  • Core fields: symbol, board, score, bias, trend, regime, support, resistance, notes, and risk flags.
  • Side effects: updates session memory for the current execution context.
  • Caller-facing delivery standard:
    • identify the data source and date window
    • treat score and bias as descriptive state summaries, not expected-return claims
    • keep the answer interpretive and current-state oriented
    • say explicitly when the result does not incorporate fundamentals, catalysts, portfolio constraints, or execution assumptions

Failure Handling

  • Parse and argument errors: non-zero exit with a readable 命令错误 message.
  • Data-loading or normalization errors: readable failure text beginning with 执行失败:.
  • Missing symbol with no reusable session symbol: readable guidance instead of a traceback.
  • If the available data window is too thin for robust interpretation, say so directly rather than pretending high confidence.

Key Rules

  • Keep this skill interpretive rather than prescriptive.
  • Use it as the clean descriptive anchor for technical-scan, decision-support, and strategy-design.
  • Do not let a scored snapshot summary masquerade as a trading instruction.
  • Do not imply indicators or controls that the current runtime does not actually expose in this skill’s local output.

Composition

  • Usually follows market-data or shares the same upstream loaders.
  • Often feeds technical-scan, decision-support, strategy-design, and market-brief.

Keep looking

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