agentii-equity-agent

agentii-equity-agent is an agent for Claude Code from agentii-ai/agentii-investment-intelligence. It costs 60 tokens per session (7,089 once invoked), scanned A, original, Apache-2.0.

An equity research agent that analyzes company filings, financial statements, valuations, risks, and market information using data from the U.S. Securities and Exchange Commission (SEC). It provides analyses with citations to source documents.

In plain words
What is it for?
Use it to research public companies, compare financial periods, assess business and industry information, study risks, and support valuation or investment reports.
Why use it?
It reduces the time spent finding and organizing information from company filings across multiple reporting periods.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions subagents; positional $N argument; mentions Claude Code.

Part of the agentii-equity-agent plugin — 9 skills, 1 agent shipped together

Good fit Use it to research public companies, compare financial periods, assess business and industry information, study risks, and support valuation or investment reports.

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Install with agentmods
npx agentmods add agents/agentii-ai/agentii-investment-intelligence/agentii-equity-agent
Install

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.

Clone the repo
git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence

Made for: Claude Code.

Or install agentii-equity-agent, the plugin that ships this one along with the rest of its 9 skills, 1 agent.

Wrote 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.

agentmods badge for agentii-equity-agent

README.md
[![agentmods](https://agentmods.dev/badge/agents/agentii-ai/agentii-investment-intelligence/agentii-equity-agent/github.svg)](https://agentmods.dev/agents/agentii-ai/agentii-investment-intelligence/agentii-equity-agent)
Your own site
<a href="https://agentmods.dev/agents/agentii-ai/agentii-investment-intelligence/agentii-equity-agent"><img src="https://agentmods.dev/badge/agents/agentii-ai/agentii-investment-intelligence/agentii-equity-agent/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.

agentmods 80×15 button for agentii-equity-agent

Your own site · 80×15
<a href="https://agentmods.dev/agents/agentii-ai/agentii-investment-intelligence/agentii-equity-agent"><img src="https://agentmods.dev/badge/agents/agentii-ai/agentii-investment-intelligence/agentii-equity-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 60 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 7,089 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00060 $0.07089
Opus 5 $0.00030 $0.03544
Sonnet 5 $0.00012 $0.01418
Haiku 4.5 $0.00006 $0.00709

Measured 5d ago against content hash 452148052631, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

agentii-equity-agent 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 5d 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.

plugins/agent-plugins/agentii-equity-agent/agents/agentii-equity-agent.md · 402 lines

How it starts

The opening of the file, as written. The whole thing — 402 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are agentii, a Senior Financial Analyst & Equity Research Specialist combining sell-side rigor, buy-side depth, and quantitative precision. Your expertise spans equity research & valuation, financial statement analysis, fundamental analysis, risk assessment, and market intelligence.

Production Grounding

The Neon production database and api.agentii.ai REST/MCP surfaces are LIVE and AUTHORITATIVE as of 2026-05-25. Production scale: 15.99M gold.xbrl_facts (with is_primary partial index), 51,089 pipeline.src_documents (100% non-null description, GIN-indexed secondary_labels), 1.34M pipeline.src_silver_pages (all 5 form types covered), 142 launch tickers at 100% processing. Always call get_ticker_coverage/{ticker} before retrieval planning. See the retrieval subagent system prompt's "Production Grounding" preamble for the full statement.

Citation-Based Addressing

Use {ticker}/{citation_id} as the canonical document locator (e.g., LLY/sec135, NVDA/sec19). UUIDs are toxic for LLM context — never expose them in user-visible prose. Page references use {ticker} {citation_id} page<N> format (e.g., LLY sec135 page12); bare integers are forbidden.

  • Layer 1: search_documents(ticker={T}, ...) returns citation_id in every row.
  • Layer 2: read_source_outline/{ticker}/{citation_id} (preferred) or legacy read_source_outline/{document_id} (UUID, deprecated).
  • Layer 3: read_source_pages/{ticker}/{citation_id}?pages=page1,page3 (preferred) or legacy UUID path.
  • For PDF sources, use ref<N> prefix (e.g., LLY/ref28); for FDA sources use fda<N> (e.g., LLY/fda245).

You have access to 19 MCP tools backed by agentii.ai's data plane — 10 years of SEC filings (10-K, 10-Q, 8-K, 6-K, 20-F) with XBRL facts, rendered statements, company profiles, earnings calendars, and keyword search across 142 launch-cohort tickers (covering 1,146-ticker registry).

Your approach is evidence-based: every conclusion grounded in official filings. You distinguish confirmed results from forecasts, perform recency validation, cite all sources, and consider multiple perspectives. You think strategically like a portfolio manager, connecting financial metrics to business dynamics and market positioning.

Read the full file on GitHub · 402 lines

Changes

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.

  1. 5d ago Changed · +2 lines · +2 tokens per session 452148052631
  2. 11d ago First seen · 400 lines · 58 tokens per session scan A df11c6ce2678

Subscribe to this mod's changes

agentii-equity-agent is an agent published in the GitHub repository agentii-ai/agentii-investment-intelligence (203 stars, last pushed yesterday), licensed Apache-2.0. It adds 60 tokens to every session and 7,089 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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