Financial Analysis Skill
Systematically perform financial analysis: ratio analysis, valuation models (DCF), and sensitivity testing to evaluate companies and investment opportunities.
The skill is purely documentation, containing no code execution, permission requests, or data collection directives. It guides users on financial analysis without requiring external API keys or transmitting sensitive data. However, it lacks any data-flow transparency, user confirmation mechanisms, or rollback options. Its dependencies (e.g., LLM, data sources) are not declared for security. Therefore, 8 points are given in the trust dimension because the main risks are visible but permissions, isolation, and recovery are incomplete.
The skill provides clear step-by-step guidance but lacks executable code or scripts, so key-path reproduction cannot be verified. There are no tests covering this skill, no error handling, or failure feedback mechanisms. Even ignoring static limitations, its reliability ceiling is low, so 5 points are given.
The skill clearly describes the goal, steps, and outputs of financial analysis, with clear scenarios (e.g., public company valuation, private investment, M&A analysis), but does not define capability boundaries or non-fit scenarios. It does not mention Chinese-language support or reachability from mainland-China networks, and core functions depend on overseas services (e.g., LLM APIs), limiting adaptability. Hence 7 points.
The skill uses standard Markdown format with methodology, steps, guidelines, and examples, but lacks installation notes, dependency notes, version numbers, changelog, maintenance responsibility, and known limitations. README provides overall framework info, but the skill itself lacks governance information. Therefore, 8 points.
The skill provides a complete set of financial analysis steps and output format, theoretically guiding the user, but lacks actual execution verification. Due to static review, direct usability of output cannot be confirmed, and the skill is more of a guide than an automated tool, limiting marginal value. Hence 5 points.
The skill has no tests, CI evidence, or third-party verification. All claims are author-written with no independent evidence. Per static assessment rules, verifiability is capped at 5, but given no verifiable material, 2 points are given.
- This skill is purely documentation with no executable code, so its actual effectiveness cannot be verified; it may function only as guidance text.
- Financial analysis involves investment decisions; the skill includes no disclaimers or user confirmation mechanisms.
- Core functionality depends on overseas services like LLM APIs, which may be unreachable from mainland-China networks.
What does this skill do, and when should you use it?
This skill guides users through comprehensive financial analysis, covering collection and verification of historical financial statements, calculation of key financial ratios, construction of multiple valuation models (DCF, comparable companies, precedent transactions), and sensitivity analysis. It emphasizes conservative assumptions, cross-validation across methods, and produces an executive summary, financial model, valuation range, investment recommendation, and supporting charts. Use cases include public company valuation, private investment evaluation, and M&A analysis.
Reads and verifies historical financial statements (income statement, balance sheet, cash flow); calculates profitability, liquidity, leverage, and efficiency ratios; builds DCF models (projecting free cash flows, determining WACC, calculating terminal value) and comparable company/precedent transaction analyses; performs scenario and sensitivity analysis; outputs an executive summary, financial model, valuation range, and investment recommendation.
- Investors evaluating a public company: provide a ticker and receive a DCF valuation and recommendation.
- Private investors assessing a startup: analyze unit economics and runway.
- M&A teams evaluating a target: assess the financial implications of an acquisition.
What are this skill's strengths and limitations?
- Provides a clear, step-by-step methodology for financial analysis
- Covers multiple valuation techniques (DCF, comps, precedent transactions)
- Emphasizes sensitivity analysis to understand key value drivers
- Cross-validates findings with multiple methods, reducing single-model bias
- No automated data collection; users must supply financial data manually or via other tools
- Skill is methodology-only; actual implementation requires user-provided tools and data
- No integration with real-time market data, which may affect timeliness
- Requires financial background to apply effectively; novices may need additional learning
How do you install this skill?
The skill is part of the Swarms repository at examples/single_agent/capabilities/skills/financial-analysis/SKILL.md. Clone the repository or download the SKILL.md file and place it in your agent skills directory (e.g., ~/.claude/skills for Claude Code) or reference it in your project. Install Swarms dependencies: pip install swarms or via uv: uv pip install swarms.
How do you use this skill?
In a skills-compatible agent, describe the task directly, e.g., 'Analyze Tesla's financials and provide a DCF valuation'. The skill guides the agent through data collection, ratio calculation, valuation modeling, sensitivity analysis, and structured output generation. Actual execution depends on the model and configured tools.