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Agent skill

Historical Financial Ratings

by OctagonAI in OctagonAI/skills

Retrieve historical financial ratings and key metric scores over time using Octagon MCP.

MITAuto-check passedBusiness, Finance & HR

Install Historical Financial Ratings

skills CLI
$ npx skills add OctagonAI/skills --skill historical-financial-ratings -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install OctagonAI/skills historical-financial-ratings --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/historical-financial-ratings .claude/skills/historical-financial-ratings && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
historical-financial-ratings
GitHub stars
127
Token cost
~1k tokens
SKILL.md length
366 words
Files
5 (incl. references)
Skills in repo
53
Repo updated
First seen
Licence
MIT

At a glance

Retrieve historical financial ratings and key metric scores over time using Octagon MCP.

  • Works in 4 steps: Identify Analysis Parameters → Execute Query via Octagon MCP → Expected Output → …
  • Analyzing overall ratings
  • SKILL.md covers Prerequisites, Workflow, Example Queries and Key Metrics Explained, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Historical Financial Ratings is an agent skill from OctagonAI/skills. Retrieve historical financial ratings and key metric scores over time using Octagon MCP. Use when analyzing overall ratings, return on assets, return on equity, discounted cash flow scores, debt-to-equity scores, and letter grades (A+, A, B, etc.) for any public company.

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `README.md`, `marketplace.json` and `references/interpreting-results.md`).

It sits in Business, Finance & HR, covering Financial modeling and MCP servers. It works with Model Context Protocol. The repository describes itself as: A collection of Claude skills for agentic financial research by Octagon. The licence is MIT.

When your agent uses it

  • Analyzing overall ratings
  • Return on assets
  • Return on equity
  • Discounted cash flow scores

Example prompts

  • “/historical-financial-ratings”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Identify Analysis Parameters
  2. Execute Query via Octagon MCP
  3. Expected Output
  4. Interpret Results

What it can do on your machine

Read from SKILL.md and the folder at commit 51e938c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are json).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Historical Financial Ratings loads about 1k tokens when it runs, and up to ~3.1k if it reads all its reference files. Until then it costs about 75 tokens; SKILL.md has 366 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~75
When it runs · the whole SKILL.md, loaded when a task matches
~1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from OctagonAI/skills at commit 51e938c, republished under its MIT licence (© OctagonAI). 366 words, ~1,016 tokens.

Download SKILL.mdSave it as .claude/skills/historical-financial-ratings/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
historical-financial-ratings
description
Retrieve historical financial ratings and key metric scores over time using Octagon MCP. Use when analyzing overall ratings, return on assets, return on equity, discounted cash flow scores, debt-to-equity scores, and letter grades (A+, A, B, etc.) for any public company.

Historical Financial Ratings

Retrieve and analyze historical financial ratings and key metric scores over time for public companies using the Octagon MCP server.

Prerequisites

Ensure Octagon MCP is configured in your AI agent (Cursor, Claude Desktop, Windsurf, etc.). See references/mcp-setup.md for installation instructions.

Workflow

1. Identify Analysis Parameters

Determine the following before querying:

  • Ticker: Stock symbol (e.g., NVDA, AAPL, MSFT)
  • Records: Number of historical data points to retrieve (e.g., 100, 500, 2000)
2. Execute Query via Octagon MCP

Use the octagon-agent tool with a natural language prompt:

Retrieve historical financial ratings and key metric scores over time for <TICKER>, limited to <N> records.

MCP Call Format:

json
{
  "server": "octagon-mcp",
  "toolName": "octagon-agent",
  "arguments": {
    "prompt": "Retrieve historical financial ratings and key metric scores over time for NVDA, limited to 2000 records."
  }
}
3. Expected Output

The agent returns historical ratings data including:

DateOverall ScoreOverall RatingROA ScoreROE ScoreDCF ScoreD/E Score
2024-01-155A+4433
2024-01-085A+4433
2023-12-295A4333
.....................

Data Sources: octagon-financials-agent

4. Interpret Results

See references/interpreting-results.md for guidance on:

  • Understanding overall scores and ratings
  • Analyzing individual metric scores
  • Identifying rating trends and changes
  • Spotting financial health improvements or deterioration

Example Queries

Standard Historical Analysis:

Retrieve historical financial ratings and key metric scores over time for NVDA, limited to 2000 records.

Recent Ratings Focus:

Retrieve historical financial ratings and key metric scores over time for AAPL, limited to 100 records.

Extended Historical View:

Retrieve historical financial ratings and key metric scores over time for MSFT, limited to 5000 records.

Key Metrics Explained

MetricDefinitionScore Range
Overall ScoreComposite financial health rating1-5 (5 = best)
Overall RatingLetter grade for financial healthA+ to F
ROA ScoreReturn on Assets efficiency1-5 (5 = best)
ROE ScoreReturn on Equity efficiency1-5 (5 = best)
DCF ScoreDiscounted Cash Flow valuation score1-5 (5 = best)
D/E ScoreDebt-to-Equity health1-5 (5 = lowest debt)
Show full SKILL.md (128 more words)Show less

Analysis Tips

  1. Consistent high scores: Companies maintaining 5-star overall scores and A+ ratings over extended periods demonstrate stable financial excellence.

  2. Score improvements: Watch for upward trends in individual metrics (ROA, ROE) as indicators of improving operational efficiency.

  3. Debt management: A stable or improving D/E score suggests the company is managing leverage responsibly.

  4. Rating downgrades: Sudden drops in overall rating (e.g., A+ to B) warrant deeper investigation into financials.

  5. Diverging metrics: If ROE is high but ROA is low, the company may be using significant leverage to boost returns.

Use Cases

  • Investment screening: Filter for companies with consistently high ratings
  • Risk monitoring: Track rating changes for portfolio holdings
  • Due diligence: Review historical financial health before investment decisions
  • Peer comparison: Compare rating trajectories across competitors

© OctagonAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references) in skills/historical-financial-ratings of OctagonAI/skills.

  • SKILL.md
  • README.md
  • marketplace.json
  • references/interpreting-results.md
  • references/mcp-setup.md

Open the folder on GitHubat commit 51e938c

Compare with similar skills

Historical Financial Ratings next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Historical Financial Ratings compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Historical Financial Ratings this skillOctagonAI/skills127—~1kAutomated safety check: PassMIT
Creating Financial ModelsChen-zexi/open-ptc-agent7293 repos~1.3kAutomated safety check: PassMIT
Tradingview MCPatilaahmettaner/tradingview-mcp5k—~1.3kAutomated safety check: PassMIT
Okx Cex Marketdex-original/okx-agent-trade-kit1101 repos~2.7kAutomated safety check: PassMIT
Polymarket Tennislivetennisapi/livetennisapi-mcp152—~3kAutomated safety check: PassMIT
Okx Sentiment Trackerdex-original/okx-agent-trade-kit1101 repos~3.8kAutomated safety check: PassMIT

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Works with

Categories

Questions about Historical Financial Ratings

What does Historical Financial Ratings do?

Retrieve historical financial ratings and key metric scores over time using Octagon MCP. Historical Financial Ratings is an agent skill from OctagonAI/skills. Retrieve historical financial ratings and key metric scores over time using Octagon MCP.

When should I use Historical Financial Ratings?

Historical Financial Ratings fits situations like: analyzing overall ratings; return on assets; return on equity; discounted cash flow scores.

How do I install Historical Financial Ratings in Claude Code?

Run `npx skills add OctagonAI/skills --skill historical-financial-ratings -a claude-code`. Or copy the skill folder (skills/historical-financial-ratings in OctagonAI/skills) into .claude/skills/historical-financial-ratings in your project. Claude Code loads it when a task matches its description.

How do I install Historical Financial Ratings in Codex?

Run `npx skills add OctagonAI/skills --skill historical-financial-ratings -a codex`. Or copy the skill folder (skills/historical-financial-ratings in OctagonAI/skills) into .agents/skills/historical-financial-ratings in your project. Codex loads it when a task matches its description.

Can I use Historical Financial Ratings in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add OctagonAI/skills --skill historical-financial-ratings -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/historical-financial-ratings, .gemini/skills/historical-financial-ratings, .github/skills/historical-financial-ratings and .opencode/skills/historical-financial-ratings in your project.

What does Historical Financial Ratings need to run?

SKILL.md names no scripts, command-line tools or credentials: Historical Financial Ratings is instructions for the agent only.

Does Historical Financial Ratings access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Historical Financial Ratings safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Historical Financial Ratings use?

Historical Financial Ratings is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Historical Financial Ratings use?

About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.1k tokens, read only when the agent opens those files.

What are the alternatives to Historical Financial Ratings?

Skills that share tags, products or a category with Historical Financial Ratings: Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars), Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars), Okx Cex Market (dex-original/okx-agent-trade-kit, 110 stars) and Polymarket Tennis (livetennisapi/livetennisapi-mcp, 152 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Historical Financial Ratings?

OctagonAI (a GitHub organization) maintains it in OctagonAI/skills, which has 127 GitHub stars. The repository holds 53 skills in this directory. The repository was last updated on June 5, 2026.

Source: OctagonAI/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.