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a-share-stock-dossiera 股股票档案

Agent Skill

a-share-stock-dossier 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

37,427

周安装

1,544

GitHub Stars

3

下载量

12,228
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:a-share-stock-dossier(a 股股票档案)
来源仓库:https://github.com/t-atlas/a-share-stock-dossier
安装命令:
openclaw skills install a-share-stock-dossier
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install a-share-stock-dossier

简介

分析师级证据优先报告,深度解析A股个股与投资组合表现。

  • 适合个股基本面复盘、行业龙头对比、盘前盘后策略制定等研究需求。
  • 整合财务数据、技术面与市场情绪,输出结构化投资建议。
  • 安装命令:openclaw skills install a-share-stock-dossier。
  • 依赖公开数据源,建议核实信息时效性与来源可靠性。

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

  1. 明日三情景(强/中/弱)触发条件 -> 动作
  2. 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.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

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按下载量换算11,862

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安装前确认

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