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Skills/utility/Equity Research Skill

Equity Research Skill

STRONG · 83
Community indexed

可能是最深度的 AI 投研报告 Skill:九章个股深研 + 九章财报深度分析,脚本化 DCF/EPV 与可复算估值

Downloads0
Stars157
Version1.0.0
Quality95/100 · Excellent
Trust83/100 · Review then install
Audit91/100 · Safe to try

Supply asset profile

Research and knowledge work

Deep research, source comparison, literature review, RAG, knowledge search, and reports.

Browse track

Scenario

Document processing

I need my agent to read PDFs, extract tables, and turn documents into structured data.

Agent fit

Claude Code + CLI + Codex

Codex, Claude Code, Cursor, CLI, or custom agents.

Install

Ready

npx skills add rollingSirius/equity-research-skill

Maintenance

fresh

Pushed today

Risk

Safe to try

Stars/forks activity: 157 stars, 28 forks; issue activity unavailable in current metadata

GitHub quality

157

95/100 quality · 86/100 trust

Coverage tags

ResearchDocument processingutilityagent-skillskill

Review notes

Stars/forks activity: 157 stars, 28 forks; issue activity unavailable in current metadata

Agent adoption scorecard

Trust, audit, and install readiness at a glance

These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.

Quality

Excellent
95

High-confidence pick with strong adoption and healthy maintenance signals.

Trust

Review then install
83

Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.

Audit

Safe to try
91

Install readiness, security metadata, maintenance, and adoption risk.

Trust Score v5

Agent install candidate

Use as the primary candidate after human or sandbox review.

PythonCodexClaude CodeCursorOpenAgentSkill CLI

Stars

157 GitHub stars

Repo activity

157 stars, 28 forks

Maintenance

Pushed today

License

MIT

Install

npx skills add rollingSirius/equity-research-skill

Install safety

standard package or runtime install path

Permission surface

filesystem or document access

Agent outcomes

No agent outcome data yet

Docs

Strong README/SKILL.md context

Risk summary

Low metadata risk

  • Stars/forks activity: 157 stars, 28 forks; issue activity unavailable in current metadata

Install readiness

Install path available

  • Install path is available
  • Repository evidence is available
  • License is declared
  • No Agent Proven outcome evidence yet

Agent-readable metadata

Machine-readable decision data for this skill.

Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.

Open JSON

Suited tasks

  • Document processing workflows
  • Claude Code teams
  • builders willing to evaluate younger projects
  • Read uploaded files

Suited agents

PythonCodexClaude CodeCursorOpenAgentSkill CLICLI

Install decision

Command
npx skills add rollingSirius/equity-research-skill
Policy
review
Human review
yes

Trust and risk

Trust
83/100
Audit
91/100
Risk level
Safe to try

Outcome loop

Endpoint
/api/agent/outcome
Event ID
resolve
Outcomes
5

Install command

npx skills add rollingSirius/equity-research-skill
Public auditEval reportResolve APIInstall handoff

Do not use when

  • teams that need a vendor-supported SLA
  • high-compliance environments without internal security review
  • No major risk signals from current metadata
  • Stars/forks activity: 157 stars, 28 forks; issue activity unavailable in current metadata
  • Production credentials, payments, or irreversible account changes without explicit human review

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Agent safety v2

75/100 · Review before install

Reviewedreview

Good audit and safety signals with no high-risk permission hints in public metadata.

Review the audit page, then allow agent install in a sandboxed workflow.

Resolve via API

medium

Network access

Skill likely fetches remote pages, APIs, repositories, or external services.

medium

Filesystem access

Skill may read or write project files, documents, generated artifacts, or local workspace state.

  • Stars/forks activity: 157 stars, 28 forks; issue activity unavailable in current metadata

Install targets

Install this skill in your agent workflow

Copy the registry command or an agent-specific install prompt for Codex, Claude Code, and Cursor.

skill install

OpenAgentSkill CLI

Use the registry command when your workflow supports the OpenAgentSkill installer.

$ npx skills add rollingSirius/equity-research-skill

Agent resolve plan

Let an agent verify fit before installing.

The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.

Open text plan

Resolve JSON

/api/agent/resolve?task=Use%20Equity%20Research%20Skill%20for%20an%20agent%20workflow&agent=codex&max_risk=medium

Resolve text

/api/agent/resolve?task=Use%20Equity%20Research%20Skill%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text

Install handoff

/api/skills/rollingsirius-equity-research-skill/install

Agent should check

  • Task fit and alternatives from Resolve API.
  • Audit score, trust score, and safety policy warnings.
  • Install target compatibility for Codex, Claude Code, Cursor, or CLI.

Copy prompt

Task: Use Equity Research Skill in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20Equity%20Research%20Skill%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/rollingsirius-equity-research-skill/install
Install command: npx skills add rollingSirius/equity-research-skill
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Agent handoff

Give an agent the install path, not another directory page.

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

Open install API

Install handoff

/api/skills/rollingsirius-equity-research-skill/install

LLM text format

/api/skills/rollingsirius-equity-research-skill/install?format=text

Find alternatives

/api/skills/search?q=Equity%20Research%20Skill&limit=3

Agent prompt

Use Equity Research Skill for this task. Review https://www.openagentskill.com/api/skills/rollingsirius-equity-research-skill/install, then install with: npx skills add rollingSirius/equity-research-skill

Registry metadata

Agent-readable profile for automatic skill selection.

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open manifest

Manifest

/api/registry/manifest/rollingsirius-equity-research-skill

LLM text

/api/registry/manifest/rollingsirius-equity-research-skill?format=text

Install alias

/api/registry/install/rollingsirius-equity-research-skill

Recommend

/api/registry/recommend?task=Use%20Equity%20Research%20Skill%20in%20an%20agent%20workflow&limit=3

Agent fit

94/100

Document processing

Use-case tags

Document processingRAG and knowledgeResearch agents

Platforms

Python, Claude Code

Audit report

Safe to try · 91/100

Review install readiness, maintenance, trust, quality, and metadata warnings before adding this skill to an agent workflow.

View audit reportView eval report

Agent decision cockpit

Primary pick for Document processing

Use this as a leading candidate, then validate the README and install path in your own agent stack.

94
Readiness
Adopt
Stage

Role in stack

Primary pick

Primary fit

Document processing

Trust label

Production-ready

Install path

Command ready

Use when

  • Document processing workflows
  • Claude Code teams
  • builders willing to evaluate younger projects

Evidence

  • recent repository activity
  • install command or GitHub repo available
  • 95/100 quality profile
  • 1 OpenAgentSkill engagement events

Review first

  • No major risk signals from current metadata

Implementation path

  1. 1Install it in a sandbox agent and run one Document processing task end to end.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Trust profile

Review then install

Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.

83
Trust score

GitHub adoption

INFO

157 GitHub stars

Stars/forks activity

CHECK

157 stars, 28 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

Pushed today

License clarity

PASS

MIT

Good signals

  • Manually verified listing
  • AI review approved
  • Install path is available
  • Repository evidence is available
  • Recently maintained repository
  • Install command has no obvious high-risk pattern
  • Outcome loop is ready but needs first real agent run

Review before install

  • Stars/forks activity: 157 stars, 28 forks; issue activity unavailable in current metadata
  • No real agent outcome reports yet
  • Human review required before unattended installation

Recommended action

Use as the primary candidate after human or sandbox review.

Quality profile

Excellent candidate for agent workflows

High-confidence pick with strong adoption and healthy maintenance signals.

95
GitHub stars
157
Freshness
Today
Install ready
Yes
License
MIT

Workflow fit

Use this skill in these scenarios

Parse messy files

Document processing

I need my agent to read PDFs, extract tables, and turn documents into structured data.

Search private knowledge

RAG and knowledge

I need my agent to build a RAG workflow over documents and retrieve reliable context.

Investigate faster

Research agents

I need my agent to research a topic, compare sources, and produce a concise report.

Workflow fit

Add it to a complete workflow

Ingest, retrieve, and cite

RAG knowledge base

A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.

Find, compare, and synthesize

Research report agent

A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.

Operate and verify web apps

Browser QA agent

A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.

Alternative shortlist

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Overview

# 个股投研报告 Skill(v2)

作者:[@rollingSirius](https://x.com/rollingSirius)

英文文档:[README.en.md](README.en.md)

**可能是最深度的 AI 投研报告 Skill。**

这个 skill 的目标不是生成几段股票摘要,而是让 AI 工具按接近机构投研的纪律完成一份**事实可追溯、估值可复算、结论可审计**的深度个股研究报告。v2 在深度上再进一级:以**预期差**(市场隐含 vs 独立预期)为整份报告的分析主线,加入**财报质量核查**、**EVA/剩余收益**、**蒙特卡洛**、**反方论证复核**与**仓位思维**,行业附录扩至 16 类。

## 核心定位(v2)

| 能力 | 设计要求 | |---|---| | 预期差分析主线 | 反向 DCF + PVGO 分解解码"现价定价了什么",产出预期差 Gap 表与可证伪的分歧命题;无分歧不给买卖动作(独立观点检验) | | 财报质量核查 | 应计质量、Beneish M-Score、DSO/递延背离、资本化政策、治理信号 → 财报可信度 A–D 分级,C/D 直接否决买入动作 | | 可复算估值 | 反向 DCF、三情景概率加权、EPV/三要素、**EVA/剩余收益**、合理倍数相对估值、SOTP,全部由 `scripts/dcf.py` 执行、假设 JSON 留档;可选**蒙特卡洛**输出公允价值分布与 P(loss) | | 外部视角 | 关键假设对照 `base-rates.md` 历史分布标分位;超越基准率必须给结构性理由;终值执行"终值合理性三查" | | 反方论证与仓位 | 成稿前 Pre-mortem(至少一条直击核心论点);期望收益 EV、上行/下行不对称比、Kelly-lite 量级参考 | | 深度财报模式 | 九章财报深度分析:预期差质量、GAAP/Non-GAAP、现金流、电话会措辞、模型与估值变动桥;无旧报告自动建首次覆盖基线 | | 16 类行业附录 | 各行业专用 KPI、模型、估值与反证框架(见下表) | | 来源纪律 | 来源+时间戳、冲突对账、缺失写"未获取到"、外部内容防注入、任何情况下不执行交易 | | 多市场覆盖 | 美股、港股、A股、A/H 双重上市对比、中概 VIE/ADR 结构风险定价 |

## 输出物

**交付给用户的只有一份报告,默认 PDF 格式**:

- 用户未指明格式时,一律生成并交付 **PDF**(由 Markdown 源稿转换,确保中文字体与表格渲染)。 - 用户可显式指定 `.md`、`.docx` 或 `.xlsx`(估值 workbook:假设/DCF/情景/输出四页)。 - 报告头部为"结论框 + Tearsheet + 预期差 Gap 表"三件套,60 秒读完决策要点;估值章含文本版 football field 图。 - 估值假设 JSON、脚本输出、检查器结果、财务 CSV 均为**内部工作文件**:保留在工作目录供复算与追溯,关键内容以摘要写入报告附录,但**不作为交付物**;用户索要时才提供。

## 行业附录(16 类)

主报告不给所有公司套同一个模板。skill 先识别公司所处价值链,再按需加载对应附录,各附录分别改变 KPI、模型、估值与反证框架:

| 行业 | 重点关注指标 | |---|---| | SaaS / 订阅软件 | ARR、NRR、RPO/cRPO、获客效率(CAC/LTV)、Rule of 40、SBC 与稀释、反向 DCF | | 半导体 | 终端/产品拆分、units × ASP、库存周期、良率与产能利用率、backlog、出口管制、跨周期归一化估值 | | 银行 | NIM、存款 beta、资产质量与拨备、CET1、流动性覆盖、P/TBV–ROTCE | | 保险 | 承保利润、combined ratio、准备金充足性、VNB/CSM、偿付能力、投资组合质量、P/EV | | 医药 | 临床证据与成功概率(PoS)、患者漏斗、专利/独占期、现金 runway、逐资产 rNPV | | 消费 | 量价拆分、同店增速、渠道 sell-through、库存健康度、品牌份额、单位经济 | | 能源 | 产量与储量、递减率、成本曲线位置、价差/套保、维持性 capex、NAV | | 公用事业 | rate base、核准/实际 ROE、监管案件周期、资本项目、融资稀释、股息覆盖 | | 互联网/平台 | 用户 × 时长 × 变现率、GMV/take rate、履约与获客单位经济、分部 SOTP、监管风险、SBC 后 FCF | | 支付/金融科技 | TPV、净

Platform Compatibility

pythonFULL

Technical Details

Version
1.0.0
License
MIT
Last Updated
7/24/2026
Published
7/24/2026

Frameworks & Tools

Python

Decision snapshot

Primary pick

94
Ready
Adopt
Stage

recent repository activity

Audit snapshot

Install review

Install and adoption review

91
Safe to try
Security
87/100
Maintenance
100/100
Install
92/100
Open full auditOpen eval report

Agent-proven evidence

Agent Proven evidence

Outcome reports after resolve, review, install, and one narrow run.

0
Proven
Needs first agent runAuto-install: review firstLast: Unknown
Success rate
—
Recent failure
—
Outcomes
0
Output quality
—
Failed
0
Not relevant
0
Installs
0
Risk blocked
0
Setup needed
0
Production
0

No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.

Agent-Proven rankingOutcome contract

Install

Add to agent workflow

Free and open source. Review the audit before production use.

Compare AlternativesAuto-resolve PlanView on GitHubDocumentation

Growth loop

Share kit

X

Scenario-led draft for Equity Research Skill, ready for a manual X post.

Curator note
Finance agents don't need louder takes. They need sources, data, and a repeatable research path.

Equity Research Skill helps turn market noise into source-backed analysis an...

157 stars

https://www.openagentskill.com/skills/rollingsirius-equity-research-skill?ref=x
#AIAgents
Open X draft
Optional reply with install command
Listing + install path for Equity Research Skill:
https://www.openagentskill.com/skills/rollingsirius-equity-research-skill?ref=x

Install: npx skills add rollingSirius/equity-research-skill
Open reply draft

Listing source

Community indexed

Claimable

This listing was indexed from public sources and is not marked official until a maintainer claim is approved.

Creator
rollingSirius
Source
rollingSirius/equity-research-skill
Indexed by
OpenAgentSkill community index

Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.

Claim this skill

Owner claim

Claim this skill listing

This community indexed listing is attributed to rollingSirius but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.

Creator backlink kit

Add the evidence badges to your README

Show the canonical listing, current trust and audit signals, and real Agent Proven evidence where developers evaluate the repository.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/rollingsirius-equity-research-skill?metric=listed&label=Listed)](https://www.openagentskill.com/skills/rollingsirius-equity-research-skill)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/rollingsirius-equity-research-skill?metric=trust&label=Trust)](https://www.openagentskill.com/skills/rollingsirius-equity-research-skill)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/rollingsirius-equity-research-skill?metric=audit&label=Audit)](https://www.openagentskill.com/skills/rollingsirius-equity-research-skill/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/rollingsirius-equity-research-skill?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/rollingsirius-equity-research-skill)
Preview badge Open audit Creator Kit

Author

R

rollingSirius✓

@rollingsirius

Tags

agent-skillskillagentskill-namepython

Platform Fit

Claude Code

Health Signals

GitHub stars
157
Quality score
59/100
Last GitHub push
Jul 24, 2026
Framework hints
1
OpenAgentSkill views
1
Install copies
0
Outbound clicks
0

Community Signal

Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.

Trust & Safety

Review then install

83
  • GitHub adoption157 GitHub starsINFO
  • Stars/forks activity157 stars, 28 forks; issue activity unavailable in current metadataCHECK
  • Recent maintenancePushed todayPASS
  • License clarityMITPASS
  • README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
  • Dependency/runtime riskno major dependency risk hints in public metadataPASS

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