zaleqzzhang

a-share-stock-dossier

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# Install this skill:
npx skills add zaleqzzhang/best-skill --skill "a-share-stock-dossier"

Install specific skill from multi-skill repository

# Description

Analyze A-share stocks and portfolios with analyst-grade, evidence-first reports. Use when the user asks for 个股分析、持仓复盘、逻辑是否还在、行业龙头、盘前/盘后策略、情绪+技术综合判断, especially when they want deep web verification and full process transparency (检索过程摘要 + 证据逐条分析) via web_search/web_fetch/browser plus Eastmoney/Tencent quote data.

# SKILL.md


name: a-share-stock-dossier
description: Analyze A-share stocks and portfolios with analyst-grade, evidence-first reports. Use when the user asks for 个股分析、持仓复盘、逻辑是否还在、行业龙头、盘前/盘后策略、情绪+技术综合判断, especially when they want deep web verification and full process transparency (检索过程摘要 + 证据逐条分析) via web_search/web_fetch/browser plus Eastmoney/Tencent quote data.


A-Share Stock Dossier

Overview

Produce professional analyst-style stock reports that are process-transparent, evidence-bound, and directly executable.
Always split conclusions into two layers:
- 产业逻辑(fundamental/industry logic)
- 交易逻辑(price/flow/sentiment logic)

Default output mode is long-form process report unless user explicitly asks for a short summary.

Workflow

Step 1) Fix scope and objective

  • Extract stock list, cost, position size, horizon (日内 / 次日 / 5-10日), and risk preference.
  • Confirm output mode:
  • 单票深挖
  • 组合分层(A/B/C)
  • 盘前执行单
  • If screenshot is provided, parse first; ask only missing fields.

Step 2) Pull structured baseline before any narrative

Run:

python skills/a-share-stock-dossier/scripts/a_share_snapshot.py \
  --codes 603618,002149,002506,002475,002729,601116,601096 \
  --with-indices --with-kline --kline-days 60 --pretty

Lock objective facts first:
- Price/pct/range/volume/turnover
- 5d/10d/20d return
- MA5/MA10/MA20/MA60 context
- Index mood and breadth proxy

Field reference:
- references/eastmoney-fields.md

Step 3) Run deep-search loop (before and during writing)

Use:
- references/source-checklist.md
- references/search-depth-protocol.md

Mandatory minimum evidence per stock:
1. Structured quote/kline data
2. One official source (CNINFO/exchange/company IR)
3. One mainstream finance source
4. One sector/leader verification source

Tool order:
- web_search discover
- web_fetch extract正文
- browser for JS-heavy/anti-bot/paginated/incomplete extraction

Step 4) Maintain retrieval log (hard requirement)

During analysis, build a step log S1..Sn.
Each step must include:
- 检索目标(why this search)
- 查询/页面(query/url)
- 摘要(1-3条关键事实)
- 来源等级(官方/主流媒体/社区)
- 对判断影响(supports/weakens/conflicts)

If a conclusion appears without supporting steps, do not keep it in final recommendations.

Step 5) Write stock analysis in fixed order

For each stock, output strictly in this order:
1. 公司业务与收入/应用场景定位
2. 当前市场叙事与叙事阶段(启动/强化/分歧/退潮)
3. 行业龙头与板块阶段(强度/轮动/分化)
4. 技术面(趋势、关键位、失效位)
5. 舆情与事件(利多/利空/争议)
6. 双逻辑判断
- 产业逻辑:在 / 弱化 / 失效
- 交易逻辑:在 / 弱化 / 失效
7. 明日三情景(强/中/弱)触发条件 -> 动作
8. 证据绑定(E1/E2/E3/E4)+ 置信度

Use template:
- references/report-template.md

Step 6) Continuous-search triggers during writing

Pause and re-search immediately if:
- only one source supports a key claim
- key event is stale (>7 days) and no update is checked
- price/volume behavior conflicts with narrative
- wording becomes uncertain(可能/大概/据说)
- sector leader list mismatches same-day board behavior

Step 7) Conflict resolution and stop rule

  • Unify basis first (timestamp, adj/non-adj, intraday/close)
  • Priority: official > exchange data > mainstream media > community
  • If unresolved, keep explicit uncertainty notes

Stop searching only when:
1. each core conclusion has >=2 sources and >=1 official/preferred source
2. recent two re-search rounds add no high-value facts
3. conflicts are either resolved or explicitly marked

Step 8) Portfolio decision + self-correction

After all stocks:
- Rank A/B/C:
- A: 产业逻辑与交易逻辑同向
- B: 产业逻辑在、交易逻辑弱
- C: 交易逻辑受损
- Give one-line portfolio action (cut/hold/wait + why)
- Add self-correction:
- 2-3 weak points in this round
- how to recalibrate thresholds next round

Output requirements (must follow)

Default to detailed analyst-report style with this top-level structure:
1. 检索过程纪要(S1..Sn)
2. 市场底色(结构化数据)
3. 逐股深度分析(证据逐条绑定)
4. 组合分层与执行重点
5. 本轮不确定性与下轮修正计划

Never output only short conclusions unless user asks explicitly.

# Supported AI Coding Agents

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Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.