peg-valuation

peg-valuation is a command for Claude Code from agentii-ai/agentii-investment-intelligence. It costs 16 tokens per session (148 once invoked), scanned A, original, Apache-2.0.

A command for valuing a company with the PEG ratio: its price-to-earnings ratio divided by its growth rate. It also applies Peter Lynch thresholds and compares the result with companies in the same sector.

In plain words
What is it for?
Use it to run PEG valuation for a US stock and save the resulting analysis as a dated Markdown file.
Why use it?
It turns a stock ticker into a consistent growth-and-price comparison instead of requiring the calculations by hand.

Command for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is See [Mode syntax](../../../docs/commands/MODE_SYNTAX.md) for `--mode=` / `--modes=` / `--peers=` invocation rules..

Part of the quantitative-analysis plugin — 5 skills, 5 commands shipped together

Good fit Use it to run PEG valuation for a US stock and save the resulting analysis as a dated Markdown file.

Compare 6 commands from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligence
agentmods
npx agentmods add commands/agentii-ai/agentii-investment-intelligence/peg-valuation

Made for: Claude Code.

Or install quantitative-analysis, the plugin that ships this one along with the rest of its 5 skills, 5 commands.

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 peg-valuation

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

Your own site · 80×15
<a href="https://agentmods.dev/commands/agentii-ai/agentii-investment-intelligence/peg-valuation"><img src="https://agentmods.dev/badge/commands/agentii-ai/agentii-investment-intelligence/peg-valuation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 148 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 $0.00016 $0.00148
Opus 5 $0.00008 $0.00074
Sonnet 5 $0.00003 $0.00030
Haiku 4.5 $0.00002 $0.00015

Measured 5d ago against content hash 1a26362b3020, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

peg-valuation 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/vertical-plugins/quantitative-analysis/commands/peg-valuation.md · 13 lines

What it actually says

Workflow

  1. Validate ticker argument.
  2. Delegate to the peg-valuation skill bundled under quantitative-analysis.
  3. Return the structured deliverable produced by the skill. Output written to {ticker}/{YYYY-MM-DD_HHMM}_peg-valuation_{affix}.md .

See Mode syntax for --mode= / --modes= / --peers= invocation rules.

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 First seen · 13 lines · 16 tokens per session scan A 1a26362b3020

Subscribe to this mod's changes

peg-valuation is a command published in the GitHub repository agentii-ai/agentii-investment-intelligence (203 stars, last pushed yesterday), licensed Apache-2.0. It adds 16 tokens to every session and 148 once invoked, about $0.0001 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 2026-09-05.