# Company Analysis > Automatically analyze a company or company-related finance situation from a short user prompt such as a company name, "analyze [company]," M&A, LBO, IPO, debt, credit, or risk requests. Use when an agent must infer the correct valuation and finance framework without asking follow-up questions, begin from market-implied expectations instead of immediate fair value, run Reverse DCF before Forward DCF for listed companies, perform web-verified data gathering and deal-radar checks, defend against hallucinations with explicit data tags and uncertainty statements, and produce a plain-text output with no markdown and no row-column tables. - Skill: `monarchjuno/company-analysis` (Agent Skill, multi-file: 4 files) - Install (CLI): `npx skillmds@latest add monarchjuno/company-analysis` - Raw SKILL.md: https://api.skillmd.com/api/skills/monarchjuno/company-analysis/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: monarchjuno (https://skillmd.com/u/monarchjuno) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/monarchjuno/company-analysis --- # Company Analysis ## Overview Use this skill to produce an IB-style investment analysis from minimal user input. Start from what the current price already implies, not from a fair-value claim, and force every valuation conclusion through verified data, explicit assumptions, and expectation decomposition. ## Quick Start - If the user provides only a company name or a short prompt such as "[Company] analyze," do not ask clarifying questions. Infer the company type and run the most appropriate workflow immediately. - For listed companies, always define the Narrative first and run Reverse DCF before Forward DCF. - Run web research before using any revenue, profit, debt, market cap, or transaction figure. - Read `references/analysis-orchestration.md` for routing logic and framework selection. - Read `references/data-integrity-and-deal-radar.md` for hallucination defense and mandatory pre-analysis searches. - Read `references/output-contract.md` for the exact output shape and plain-text rules. ## Core Workflow ### 1. Route the request automatically - Infer the requested analysis from the prompt without follow-up questions. - Use the default listed-company stack when the intent is ambiguous: Narrative, Reverse DCF, Forward DCF, Trading Comps, Sensitivity, and So What. - Use the framework-routing rules in `references/analysis-orchestration.md`. ### 2. Gather and tag data before modeling - Search the web for actual disclosed financial data before using any revenue, earnings, debt, or valuation number. - Tag every number as `[Actual]`, `[Estimated]`, or `[Assumption]`. - Never label a number as `[Actual]` unless the underlying source has been verified and cited. - State uncertainty explicitly whenever the data is unavailable, stale, private, disputed, or not yet reported. ### 3. Run Deal Radar before valuation - Search for pending M&A, subsidiary or parent transactions, competitor deals, regulatory or antitrust issues, activism or breakup pressure, and major shareholder ownership changes. - Distinguish rumor, official announcement, and active regulatory review. - Include only web-verified items with cited sources. ### 4. Start from Narrative and Expectations - Define the story the market is pricing into the current stock or enterprise value. - Translate that story into growth, margin, and reinvestment expectations. - Run Reverse DCF before any Forward DCF for listed companies. - Test whether the implied expectations are realistic relative to industry structure and operating history. ### 5. Run the relevant framework stack - Use DCF on an FCFF basis when the business supports a cash-flow view and the data is sufficient. - Use Trading Comps to interpret compressed expectations through multiples, not as a standalone verdict. - Use SOTP for holding companies, conglomerates, or businesses with clearly separable segments. - Use Sensitivity and Scenario Analysis for all major valuation outputs. - Use M&A, LBO, IPO, Credit, or Operating Model frameworks when the prompt directly calls for them. ### 6. Translate valuation into decision language - State what the current price requires, not just what your model says. - Quantify the growth CAGR, EBIT margin, and reinvestment rate needed to justify the current price when the expectation gap matters. - If your implied value and the current market value differ by more than 30 percent, mark it as caution and explain why. ### 7. Output in the required format - Do not use markdown. - Do not use row-column tables. - Use the required plain-text block order defined in `references/output-contract.md`. ## Mandatory Rules - Do not ask clarifying questions before producing the analysis. - Do not fabricate data, comps, transactions, or deal rumors. - Do not skip Reverse DCF for listed companies. - Do not output unsupported certainty when the underlying information is incomplete. - Do not present a fair value first and expectations second. ## Guardrails - If disclosed financial data cannot be found, say so clearly and explain that the user can provide direct inputs for a more accurate model. - If you switch into a hypothetical scenario, mark it as a non-actual example scenario. - If peer multiples or transaction data cannot be verified, state that Bloomberg, Capital IQ, or equivalent verification is needed. - If private-company financials are not disclosed, state the uncertainty instead of backfilling missing numbers as facts.