Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add OctagonAI/skills --skill sec-amendments-reviewgit clone --depth 1 https://github.com/OctagonAI/skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/octagonai/skills/sec-amendments-review)<a href="https://agentmods.dev/skills/octagonai/skills/sec-amendments-review"><img src="https://agentmods.dev/badge/skills/octagonai/skills/sec-amendments-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/octagonai/skills/sec-amendments-review"><img src="https://agentmods.dev/badge/skills/octagonai/skills/sec-amendments-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00062 | $0.01944 |
| Opus 5 | $0.00031 | $0.00972 |
| Sonnet 5 | $0.00012 | $0.00389 |
| Haiku 4.5 | $0.00006 | $0.00194 |
Grade A, and why
sec-amendments-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SEC Amendments Review
Review amendments to SEC filings and identify material changes or corrections 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)
- Time Period (optional): Recent amendments, specific date range
- Filing Type (optional): Specific amendment types of interest
2. Execute Query via Octagon MCP
Use the octagon-agent tool with a natural language prompt:
Review recent amendments to SEC filings for <TICKER> and identify material changes or corrections.
MCP Call Format:
{
"server": "octagon-mcp",
"toolName": "octagon-agent",
"arguments": {
"prompt": "Review recent amendments to SEC filings for AMZN and identify material changes or corrections."
}
}
3. Expected Output
The agent returns structured amendment analysis including:
Recent Amendments:
- Form 144/A: Amended report of proposed securities sales
- Filing date and description
- Material changes identified
Related Filings:
- Original filings being amended
- Subsequent transactions (e.g., bond offerings)
Data Sources: octagon-sec-agent, octagon-web-search-agent
4. Interpret Results
See references/interpreting-results.md for guidance on:
- Understanding amendment types
- Assessing materiality of changes
- Tracking restatement patterns
- Evaluating correction significance
Example Queries
General Amendment Review:
Review recent amendments to SEC filings for AMZN and identify material changes or corrections.
10-K Amendments:
Has TSLA filed any 10-K/A amendments in the past year and what changes were made?
Restatement Search:
Identify any financial restatements or 10-Q/A amendments filed by META in 2025.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 318 lines · 62 tokens per session scan A f6d5c5b44837
sec-amendments-review is a skill published in the GitHub repository OctagonAI/skills (127 stars, last pushed 3mo ago), licensed MIT. It adds 62 tokens to every session and 1,944 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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