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Ratio Analysis

Community
agentii-ai
ratio-analysis

Financial ratio analysis, profitability ratios ROE ROA ROIC, liquidity ratios current quick cash, leverage ratios debt-to-equity interest coverage, efficiency ratios asset turnover inventory turnover DSO, valuation ratios PE PB EV/EBITDA, cross-company ratio comparison, DuPont analysis

Overview

Publisheragentii-ai
Repositoryagentii-investment-intelligence
Skill nameratio-analysis
Stars
207
Forks
16
Bundled files
7
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by agentii-ai on GitHub. Read the source before you install it.

Installation

Install the Ratio Analysis AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/quantitative-analysis/skills/agentii/ratio-analysis
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence.git /tmp/agentii-investment-intelligence
mkdir -p .claude/skills
cp -r /tmp/agentii-investment-intelligence/plugins/vertical-plugins/quantitative-analysis/skills/agentii/ratio-analysis .claude/skills/ratio-analysis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ratio Analysis in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ratio Analysis on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ratio Analysis is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Financial Ratio Analysis

Quantitative skill computing 6 categories of financial ratios from XBRL financial data. Cross-company comparison within sector. References professional financial training ratio interpretation standards.

Preflight

Run canonical pre-flight per contracts/preflight.md.

**get_realtime_quote availability **: If get_realtime_quote is not yet deployed in the MCP surface, use search_earnings_calendar for PE/earnings data and flag valuation ratios as "current price unavailable — using latest reported data." Prompts user for current stock price as manual fallback.

Include the X-Agentii-Trace header on every tool call per contracts/x-agentii-trace-header.md — carry the _run_id from your first tool result and name yourself (and your parent, if you were spawned).

Triggers

  • analyze financial ratios for {ticker}
  • ratio analysis {ticker}
  • compute profitability ratios {ticker}
  • liquidity analysis {ticker}
  • leverage analysis {ticker}
  • efficiency ratios {ticker}
  • valuation ratios {ticker}
  • DuPont analysis {ticker}
  • cross-company ratio comparison {ticker}
  • compare {ticker} ratios to peers

Defaults

ParameterDefaultNotes
lookback_quarters4Trailing 4 quarters for current ratios
include_peerstrueCross-company comparison within sector
ratio_categoriesallprofitability, liquidity, leverage, efficiency, valuation, growth

Methodology

Retrieval Scope

structured_only — this skill computes ratios from XBRL financial data and real-time price data. No unstructured document search required. All data sources are queryable via agentii MCP tools.

Retrieval Strategy

See contracts/retrieval.md for the canonical decision tree; skill-specific retrieval detail is in references/methodology.md.

Temporal Scope

Default: 4 fiscal quarters (max 12). Ratio analysis uses trailing 4 quarters for current snapshot; up to 12 quarters for trend analysis.

Tool Allowlist

See frontmatter allowed_tools. search_xbrl_facts is the primary data source for financial statement line items. get_realtime_quote provides current stock price for valuation ratios (P/E, P/B, P/S). search_companies enables peer identification for cross-company comparison.

Protocol

Step-by-step execution detail is in references/methodology.md.

ROIC Analysis: When computing Return on Invested Capital, apply the institutional-grade framework in references/roic-methodology.md. Use the four-variant approach (excluding/including goodwill × with/without intangible capitalization) appropriate to the analytical question, industry-specific capitalization rates per the academic framework, ROIIC over rolling 3-year periods, and DuPont decomposition to map ROIC to competitive strategy. Is the company passing the one dollar test?

Ratio Definitions

Full ratio formula definitions are in references/methodology.md.

Output File

Write the final deliverable to {ticker}/{YYYY-MM-DD_HHMM}_ratio-analysis_{affix}.md . Example affixes: profitability, liquidity-leverage, peer-comparison.

Output Structure

The deliverable is a structured markdown report written to the path in ## Output File. Full section-by-section template (headings, tables, and field definitions) lives in references/output-structure.md. Required elements:

  1. Executive Summary — headline conclusions (≤200 words).
  2. Core analysis sections — per this skill's methodology and analyst modes.
  3. Data classification — tag findings [FACT] / [DEDUCTED] / [VIEW] per contracts/snapshot-synthesis.md.
  4. Coverage Gaps & Citations — inline /v/ citations are PRIMARY (immediately after each fact); the bottom Citations section is a non-duplicative roll-up index.
  5. Output frontmatter — emit the FR-090 structured block per contracts/output-frontmatter-schema.md.

Citations & memory: follow contracts/citation-and-memory.md — ≥1 citation per 200 words; every material fact, table row, and metric is immediately followed by its inline clickable https://agentii.ai/v/{ticker}/{citation_id}/{N} link; a bottom Citations section provides a non-duplicative roll-up index; the closing TUI reply includes a compact Key Citations list (headline 5–10 facts) of clickable /v/ URLs; and append the run to agentii.md per contracts/agentii-md-schema.md.

Tool Fallbacks

Per-tool failure modes and fallback actions are tabulated in references/tool-fallbacks.md.

Memory & Snapshot

  • Memory load (pre-flight): load prior workspace context for the ticker before retrieval — see contracts/memory-load.md.
  • Structured output frontmatter: emit the FR-090 block (key_metrics, conclusions, facts_count, deducted_count, views_count, citation_count) per contracts/output-frontmatter-schema.md.
  • Snapshot synthesis: after writing the deliverable, update the two-tier snapshot and classify findings as [FACT]/[DEDUCTED]/[VIEW] — see contracts/snapshot-synthesis.md.
  • Session archival: record the run under sessions/{YYYY-MM-DD}/ and update sessions/INDEX.md per contracts/session-format.md.

Final Summary (TUI)

End the closing chat reply with a compact Key Citations list (headline 5–10 facts), each a clickable https://agentii.ai/v/{ticker}/{citation_id}/{N} link, so the user can cmd+click straight to the exact SEC page. See contracts/citation-and-memory.md.

Error Handling

Failure ModeDetectionActionUser-Facing Message
Missing dataXBRL returns empty for key conceptsWiden date range and retry once"No financial data available for {ticker} in requested window."
Non-USD currencyunit field is not USDAnnotate with ISO 4217 code"⚠ {ticker} reports in {currency}. Ratios computed in reporting currency."
Peer data incomplete<3 peers have comparable dataReduce peer set; flag incomplete peers"Cross-company comparison based on {n} of {m} peers with complete data."
MCP unreachablePreflight probe failsHalt with actionable error"agentii data plane unreachable; check connection."

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ratio Analysis AI skill do?

Financial ratio analysis, profitability ratios ROE ROA ROIC, liquidity ratios current quick cash, leverage ratios debt-to-equity interest coverage, efficiency ratios asset turnover inventory turnover DSO, valuation ratios PE PB EV/EBITDA, cross-company ratio comparison, DuPont analysis

Why use Ratio Analysis on TypingMind?

Because you install it once and use it with any model. Ratio Analysis is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ratio Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/vertical-plugins/quantitative-analysis/skills/agentii/ratio-analysis. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ratio Analysis?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ratio Analysis?

As many as you like. As long as a model supports skills, you can use Ratio Analysis with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ratio Analysis AI skill free?

Yes. It is published on GitHub by agentii-ai under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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