Agent skill

Sec Footnotes Analysis

by OctagonAI in OctagonAI/skills

Analyze footnotes and accounting policies from SEC filings using Octagon MCP.

MITAuto-check passedBusiness, Finance & HR

Install Sec Footnotes Analysis

skills CLI
$ npx skills add OctagonAI/skills --skill sec-footnotes-analysis -a claude-code

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

GitHub CLI
$ gh skill install OctagonAI/skills sec-footnotes-analysis --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/sec-footnotes-analysis .claude/skills/sec-footnotes-analysis && 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
sec-footnotes-analysis
GitHub stars
127
Token cost
~1.9k tokens
SKILL.md length
635 words
Files
5 (incl. references)
Skills in repo
53
Repo updated
First seen
Licence
MIT

At a glance

Analyze footnotes and accounting policies from SEC filings using Octagon MCP.

  • Works in 4 steps: Identify Analysis Parameters → Execute Query via Octagon MCP → Expected Output → …
  • Researching revenue recognition policies
  • SKILL.md covers Prerequisites, Workflow, Example Queries and Key Footnote Categories, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Sec Footnotes Analysis is an agent skill from OctagonAI/skills. Analyze footnotes and accounting policies from SEC filings using Octagon MCP. Use when researching revenue recognition policies, critical estimates, lease obligations, pension assumptions, stock compensation, contingencies, and new accounting pronouncements.

Its SKILL.md is about 1.9k 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 Accounting and bookkeeping and MCP servers. It works with Model Context Protocol and SEC EDGAR. 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

  • Researching revenue recognition policies
  • Critical estimates
  • Lease obligations
  • Pension assumptions

Example prompts

  • “/sec-footnotes-analysis”

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

Sec Footnotes Analysis loads about 1.9k tokens when it runs, and up to ~4.5k if it reads all its reference files. Until then it costs about 70 tokens; SKILL.md has 635 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~70
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.5k

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). 635 words, ~1,852 tokens.

Download SKILL.mdSave it as .claude/skills/sec-footnotes-analysis/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
sec-footnotes-analysis
description
Analyze footnotes and accounting policies from SEC filings using Octagon MCP. Use when researching revenue recognition policies, critical estimates, lease obligations, pension assumptions, stock compensation, contingencies, and new accounting pronouncements.

SEC Footnotes Analysis

Analyze footnotes and accounting policies from SEC filings 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., AAPL, MSFT, GOOGL)
  • Filing Type (optional): 10-K (annual) or 10-Q (quarterly)
  • Focus Area (optional): Specific footnote topics of interest
2. Execute Query via Octagon MCP

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

Analyze the footnotes and accounting policies from <TICKER>'s latest quarterly filing.

MCP Call Format:

json
{
  "server": "octagon-mcp",
  "toolName": "octagon-agent",
  "arguments": {
    "prompt": "Analyze the footnotes and accounting policies from NVDA's latest quarterly filing."
  }
}
3. Expected Output

The agent returns structured footnote analysis including:

Accounting Consistency:

  • No material changes to significant accounting policies since annual report

Fiscal Year Structure:

  • 52-week fiscal year ending last Sunday in January
  • Q3 is a 13-week quarter

Consolidation Principles:

  • Includes wholly owned subsidiaries
  • Intercompany balances eliminated

Estimates and Assumptions:

  • Management estimates that could differ from actual results

New Accounting Pronouncements:

  • No recent adoptions materially impacting statements

Data Sources: octagon-sec-agent

4. Interpret Results

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

  • Understanding key footnote disclosures
  • Evaluating accounting policy changes
  • Assessing critical estimates
  • Identifying hidden risks

Example Queries

Full Footnote Analysis:

Analyze the footnotes and accounting policies from NVDA's latest quarterly filing.

Revenue Recognition:

Extract the revenue recognition policies and performance obligations from MSFT's latest 10-K footnotes.

Lease Obligations:

Analyze the lease footnotes and operating lease obligations from AMZN's latest 10-K.

Debt Details:

Extract debt maturity schedule and terms from AAPL's footnotes in the latest 10-K.

Stock Compensation:

Analyze the stock-based compensation footnotes for GOOGL including vesting schedules and expense.

Contingencies:

Extract litigation and contingency disclosures from META's latest 10-K footnotes.

Key Footnote Categories

Significant Accounting Policies (Note 1/2)
PolicyWhat It Covers
Revenue RecognitionWhen and how revenue is recognized
ConsolidationSubsidiaries, VIEs, eliminations
Cash EquivalentsDefinition, components
InventoryValuation method (FIFO, LIFO, avg)
Property & EquipmentDepreciation methods, useful lives
IntangiblesAmortization, impairment testing
LeasesClassification, measurement
Income TaxesDeferred taxes, uncertain positions
Revenue Recognition
ElementDisclosure
Performance ObligationsDistinct goods/services
Transaction PriceAllocation methodology
TimingPoint in time vs. over time
Contract Assets/LiabilitiesDeferred revenue, unbilled
DisaggregationRevenue by type, geography
Fair Value Measurements
LevelDescription
Level 1Quoted prices in active markets
Level 2Observable inputs other than Level 1
Level 3Unobservable inputs
Debt and Financing
DisclosureContent
TermsInterest rates, covenants
MaturitiesRepayment schedule
Fair ValueCarrying vs. market value
Credit FacilitiesAvailability, usage
Leases
ElementDisclosure
ClassificationOperating vs. finance
ROU AssetsRight-of-use asset values
Lease LiabilitiesPresent value of payments
Maturity ScheduleFuture payment obligations
ExpenseLease cost breakdown
Commitments and Contingencies
TypeDisclosure
LegalLitigation status, reserves
PurchaseContractual obligations
GuaranteesIndemnifications, warranties
EnvironmentalRemediation, compliance
Stock Compensation
ElementDisclosure
Plan DescriptionTypes of awards
ExpensePeriod cost recognized
ValuationAssumptions (volatility, term)
Unvested AwardsOutstanding, expected vesting
Show full SKILL.md (244 more words)Show less

Critical Accounting Estimates

High Judgment Areas
EstimateRisk Factors
GoodwillImpairment testing assumptions
RevenueVariable consideration, returns
AllowancesBad debt, inventory obsolescence
TaxesUncertain positions, valuation allowance
ContingenciesLitigation outcomes, timing
PensionsDiscount rate, return assumptions
Red Flags in Estimates
  1. Aggressive assumptions - Below-market discount rates
  2. Inconsistent changes - Estimate revisions without explanation
  3. Concentrated judgment - Single estimate driving results
  4. Lack of disclosure - Vague sensitivity analysis
  5. Trend divergence - Estimates moving opposite to peers

New Accounting Standards

Recently Adopted

Track impact of:

  • Revenue recognition (ASC 606)
  • Leases (ASC 842)
  • Credit losses (ASC 326)
  • Income taxes (various)
Pending Adoption

Monitor upcoming:

  • Segment reporting changes
  • Crypto asset disclosure
  • Climate-related disclosures
  • Income tax transparency

Comparing Footnotes

Year-over-Year Changes
Change TypeSignificance
New policySignificant event or standard
Policy modificationChanged circumstances
Removed disclosureIssue resolved or consolidated
Expanded disclosureIncreased materiality
Reduced disclosureDecreased significance
Peer Comparison

Compare across competitors:

  • Revenue recognition approaches
  • Estimate methodologies
  • Disclosure quality
  • Policy choices

Analysis Tips

  1. Start with Note 1: Summary of significant policies provides foundation.

  2. Track changes: Compare footnotes year-over-year for policy shifts.

  3. Read related party: Transactions with insiders reveal governance.

  4. Check subsequent events: Post-period events may be material.

  5. Cross-reference MD&A: Management discussion provides context.

  6. Note judgmental areas: High-estimate disclosures signal risk.

Use Cases

  • Accounting research: Understand company's financial reporting
  • Risk assessment: Identify hidden liabilities and contingencies
  • Valuation support: Gather inputs for financial modeling
  • Due diligence: Comprehensive policy review
  • Audit analysis: Evaluate disclosure quality

© 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/sec-footnotes-analysis 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

Sec Footnotes Analysis 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.

Sec Footnotes Analysis compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Sec Footnotes Analysis this skillOctagonAI/skills127—~1.9kAutomated safety check: PassMIT
Datapack Builderw95/awesome-claude-corporate-skills2441 repos~6kAutomated safety check: PassMIT
Odoo Agency Fleet Reviewerpipe-org/mcp-odoo421—~699Automated safety check: PassMIT
MCP Session Lifecyclenteract/nteract179—~2.9kAutomated safety check: PassBSD-3-Clause
Igce Builder Craiskillstore/marketplace433—~4.2kAutomated safety check: PassNone
Tradingview MCPatilaahmettaner/tradingview-mcp5k—~1.3kAutomated safety check: PassMIT

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Questions about Sec Footnotes Analysis

What does Sec Footnotes Analysis do?

Analyze footnotes and accounting policies from SEC filings using Octagon MCP. Sec Footnotes Analysis is an agent skill from OctagonAI/skills. Analyze footnotes and accounting policies from SEC filings using Octagon MCP.

When should I use Sec Footnotes Analysis?

Sec Footnotes Analysis fits situations like: researching revenue recognition policies; critical estimates; lease obligations; pension assumptions.

How do I install Sec Footnotes Analysis in Claude Code?

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

How do I install Sec Footnotes Analysis in Codex?

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

Can I use Sec Footnotes Analysis 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 sec-footnotes-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sec-footnotes-analysis, .gemini/skills/sec-footnotes-analysis, .github/skills/sec-footnotes-analysis and .opencode/skills/sec-footnotes-analysis in your project.

What does Sec Footnotes Analysis need to run?

SKILL.md names no scripts, command-line tools or credentials: Sec Footnotes Analysis is instructions for the agent only.

Does Sec Footnotes Analysis 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 Sec Footnotes Analysis 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 Sec Footnotes Analysis use?

Sec Footnotes Analysis 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 Sec Footnotes Analysis use?

About 1.9k tokens (SKILL.md is roughly 7.4k 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 2.7k tokens, read only when the agent opens those files.

What are the alternatives to Sec Footnotes Analysis?

Skills that share tags, products or a category with Sec Footnotes Analysis: Datapack Builder (w95/awesome-claude-corporate-skills, 244 stars), Odoo Agency Fleet Review (erpipe-org/mcp-odoo, 421 stars), MCP Session Lifecycle (nteract/nteract, 179 stars) and Igce Builder Cr (aiskillstore/marketplace, 433 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Sec Footnotes Analysis?

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.