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cs-financial-analystcs 金融分析师

Agent Skill

cs-financial-analyst 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

11,470

周安装

464

GitHub Stars

公开资料未说明

下载量

3,601
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:cs-financial-analyst(cs 金融分析师)
来源仓库:https://github.com/alirezarezvani/cs-financial-analyst
安装命令:
openclaw skills install cs-financial-analyst
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 cs-financial-analyst

简介

执行财务比率分析、cs-financial-analyst 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

  • DCF 评估和预算差异分析以支持战略决策。
  • 适用于构建滚动预测和进行投资评估场景。
  • 通过 clawhub 安装,适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • 建议确认权限与维护状态后再使用。

SKILL.md

name
financial-analyst
description
Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making. Use when analyzing financial statements, building valuation models, assessing budget variances, or constructing financial projections and forecasts. Also applicable when users mention financial modeling, cash flow analysis, company valuation, financial projections, or spreadsheet analysis.

Financial Analyst Skill

Overview

Production-ready financial analysis toolkit providing ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction. Designed for financial modeling, forecasting & budgeting, management reporting, business performance analysis, and investment analysis.

5-Phase Workflow

Phase 1: Scoping

  • Define analysis objectives and stakeholder requirements
  • Identify data sources and time periods
  • Establish materiality thresholds and accuracy targets
  • Select appropriate analytical frameworks

Phase 2: Data Analysis & Modeling

  • Collect and validate financial data (income statement, balance sheet, cash flow)
  • Validate input data completeness before running ratio calculations (check for missing fields, nulls, or implausible values)
  • Calculate financial ratios across 5 categories (profitability, liquidity, leverage, efficiency, valuation)
  • Build DCF models with WACC and terminal value calculations; cross-check DCF outputs against sanity bounds (e.g., implied multiples vs. comparables)
  • Construct budget variance analyses with favorable/unfavorable classification
  • Develop driver-based forecasts with scenario modeling

Phase 3: Insight Generation

  • Interpret ratio trends and benchmark against industry standards
  • Identify material variances and root causes
  • Assess valuation ranges through sensitivity analysis
  • Evaluate forecast scenarios (base/bull/bear) for decision support

Phase 4: Reporting

  • Generate executive summaries with key findings
  • Produce detailed variance reports by department and category
  • Deliver DCF valuation reports with sensitivity tables
  • Present rolling forecasts with trend analysis

Phase 5: Follow-up

  • Track forecast accuracy (target: +/-5% revenue, +/-3% expenses)
  • Monitor report delivery timeliness (target: 100% on time)
  • Update models with actuals as they become available
  • Refine assumptions based on variance analysis

Tools

1. Ratio Calculator (scripts/ratio_calculator.py)

Calculate and interpret financial ratios from financial statement data.

Ratio Categories:

  • Profitability: ROE, ROA, Gross Margin, Operating Margin, Net Margin
  • Liquidity: Current Ratio, Quick Ratio, Cash Ratio
  • Leverage: Debt-to-Equity, Interest Coverage, DSCR
  • Efficiency: Asset Turnover, Inventory Turnover, Receivables Turnover, DSO
  • Valuation: P/E, P/B, P/S, EV/EBITDA, PEG Ratio
python scripts/ratio_calculator.py sample_financial_data.json
python scripts/ratio_calculator.py sample_financial_data.json --format json
python scripts/ratio_calculator.py sample_financial_data.json --category profitability

2. DCF Valuation (scripts/dcf_valuation.py)

Discounted Cash Flow enterprise and equity valuation with sensitivity analysis.

Features:

  • WACC calculation via CAPM
  • Revenue and free cash flow projections (5-year default)
  • Terminal value via perpetuity growth and exit multiple methods
  • Enterprise value and equity value derivation
  • Two-way sensitivity analysis (discount rate vs growth rate)
python scripts/dcf_valuation.py valuation_data.json
python scripts/dcf_valuation.py valuation_data.json --format json
python scripts/dcf_valuation.py valuation_data.json --projection-years 7

3. Budget Variance Analyzer (scripts/budget_variance_analyzer.py)

Analyze actual vs budget vs prior year performance with materiality filtering.

Features:

  • Dollar and percentage variance calculation
  • Materiality threshold filtering (default: 10% or $50K)
  • Favorable/unfavorable classification with revenue/expense logic
  • Department and category breakdown
  • Executive summary generation
python scripts/budget_variance_analyzer.py budget_data.json
python scripts/budget_variance_analyzer.py budget_data.json --format json
python scripts/budget_variance_analyzer.py budget_data.json --threshold-pct 5 --threshold-amt 25000

4. Forecast Builder (scripts/forecast_builder.py)

Driver-based revenue forecasting with rolling cash flow projection and scenario modeling.

Features:

  • Driver-based revenue forecast model
  • 13-week rolling cash flow projection
  • Scenario modeling (base/bull/bear cases)
  • Trend analysis using simple linear regression (standard library)
python scripts/forecast_builder.py forecast_data.json
python scripts/forecast_builder.py forecast_data.json --format json
python scripts/forecast_builder.py forecast_data.json --scenarios base,bull,bear

Knowledge Bases

ReferencePurpose
references/financial-ratios-guide.mdRatio formulas, interpretation, industry benchmarks
references/valuation-methodology.mdDCF methodology, WACC, terminal value, comps
references/forecasting-best-practices.mdDriver-based forecasting, rolling forecasts, accuracy
references/industry-adaptations.mdSector-specific metrics and considerations (SaaS, Retail, Manufacturing, Financial Services, Healthcare)

Templates

TemplatePurpose
assets/variance_report_template.mdBudget variance report template
assets/dcf_analysis_template.mdDCF valuation analysis template
assets/forecast_report_template.mdRevenue forecast report template

Key Metrics & Targets

MetricTarget
Forecast accuracy (revenue)+/-5%
Forecast accuracy (expenses)+/-3%
Report delivery100% on time
Model documentationComplete for all assumptions
Variance explanation100% of material variances

Input Data Format

All scripts accept JSON input files. See assets/sample_financial_data.json for the complete input schema covering all four tools.

Dependencies

None - All scripts use Python standard library only (math, statistics, json, argparse, datetime). No numpy, pandas, or scipy required.

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

OpenClaw

96.75%
按下载量换算3,484

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install cs-financial-analyst 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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