plan-equity-portfolio

plan-equity-portfolio is a skill for Claude Code, Codex from AlvisoOculus/optionsahoy-mcp. It costs 113 tokens per session (1,326 once invoked), scanned A, original, MIT.

A planning guide for people who hold several kinds of company equity, such as ISOs, NSOs, RSUs, and company stock.

In plain words
What is it for?
Use it to plan what to do across multiple grants and holdings, including exercise timing, selling, tax exposure, and stock concentration.
Why use it?
It combines interacting decisions into one ordered plan, since one action can affect taxes, cash needs, and the risks of another.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it to plan what to do across multiple grants and holdings, including exercise timing, selling, tax exposure, and stock concentration.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/alvisooculus/optionsahoy-mcp/plan-equity-portfolio
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.

Any agent
npx skills add AlvisoOculus/optionsahoy-mcp --skill plan-equity-portfolio
Clone the repo
git clone --depth 1 https://github.com/AlvisoOculus/optionsahoy-mcp

Made for: Claude Code, Codex.

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 plan-equity-portfolio

README.md
[![agentmods](https://agentmods.dev/badge/skills/alvisooculus/optionsahoy-mcp/plan-equity-portfolio/github.svg)](https://agentmods.dev/skills/alvisooculus/optionsahoy-mcp/plan-equity-portfolio)
Your own site
<a href="https://agentmods.dev/skills/alvisooculus/optionsahoy-mcp/plan-equity-portfolio"><img src="https://agentmods.dev/badge/skills/alvisooculus/optionsahoy-mcp/plan-equity-portfolio/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 plan-equity-portfolio

Your own site · 80×15
<a href="https://agentmods.dev/skills/alvisooculus/optionsahoy-mcp/plan-equity-portfolio"><img src="https://agentmods.dev/badge/skills/alvisooculus/optionsahoy-mcp/plan-equity-portfolio.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 113 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,326 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 $0.00113 $0.01326
Opus 5 $0.00056 $0.00663
Sonnet 5 $0.00023 $0.00265
Haiku 4.5 $0.00011 $0.00133

Measured 11d ago against content hash 22a66258b497, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

plan-equity-portfolio 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 11d 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.

integrations/agent-kits/chatgpt-skill/plan-equity-portfolio/SKILL.md · 70 lines

How it starts

The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Plan an equity portfolio

The individual OptionsAhoy calculators each answer one decision exactly. This skill covers the case they do not: a person holding several grant types at once, where the decisions interact. Exercising ISOs raises alternative minimum tax (AMT) exposure in a year when selling RSUs would also raise ordinary income, and both compete for the same cash.

Your job is to sequence the calls, ask for missing inputs once rather than piecemeal, and hand back one ordered plan.

Never do the tax math yourself

Every number in your answer must come from a tool call. A published five-model benchmark on a single multi-year ISO problem found every run that returned a schedule overstated its own after-tax result by 1.6 to 17.6 times against the provable optimum. One model claimed $3.9M, $5.2M, and $13.0M on three runs of identical input. You are not exempt from this. Estimating "roughly" a tax figure is the failure mode, not a shortcut.

Step 1: take inventory before calling anything

Ask one consolidated question covering what you are missing. Do not ask field by field across several turns.

You need, for the person: filing status, state of residence, and annual ordinary income. For each holding: the instrument (ISO, NSO, RSU vested, RSU unvested, owned shares), share counts, strike or cost basis, grant or vest dates, and the current share price. If the company is public and covered, the ticker alone resolves expected growth and volatility, so ask for it first and skip those two.

Ask also what the money is for. A person diversifying has a different plan from one funding a house down payment by a date, and the second needs a target amount and deadline.

If someone volunteers only part of this, work with what they gave and name the gap in your answer rather than stalling.

Step 2: call the calculators, one decision at a time

Holding or goal Tool
ISOs, any exercise timing question amt_iso_optimize
NSOs nso_calculate
RSUs at or near vest rsu_sell_vs_hold
Vested RSU lots being sold down rsu_lot_optimize
Concentration in one stock concentration_analyze
Hedging an existing position protective_put_price
A cash target by a date equity_funding_plan
Possible Section 1202 stock qsbs_check

Read the full file on GitHub · 70 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. 11d ago First seen · 70 lines · 113 tokens per session scan A 22a66258b497

Subscribe to this mod's changes

plan-equity-portfolio is a skill published in the GitHub repository AlvisoOculus/optionsahoy-mcp (5 stars, last pushed 4d ago), licensed MIT. It adds 113 tokens to every session and 1,326 once invoked, about $0.0006 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 2026-08-31.

Related

Other skills, from other repositories

x402-list

Discover x402 payment services and on-chain-verified facilitator settlement volume via the x402-list directory. Use when a user or agent needs to find an API/service that accepts x402 (HTTP 402 stablecoin) payments, compare services by reliability and price, check service uptime/health, see whether a service has…

mcccsm/x402-list-mcp · 99 tokens

second-order-thinking

Think beyond immediate consequences to understand the chain reactions of decisions. Master Howard Marks' investment framework for seeing what others miss. Use when: Strategic decisions where long-term consequences matter; Policy/rule changes that will trigger behavioral responses; Competitive moves to anticipate…

guia-matthieu/clawfu-skills · 82 tokens

forecast-scenarios

Model best-case, worst-case, and likely revenue scenarios with sensitivity analysis for strategic planning. Use when: building financial forecasts; presenting board scenarios; planning headcount around revenue uncertainty; modeling pricing changes impact; preparing investor updates with upside/downside ranges.

guia-matthieu/clawfu-skills · 54 tokens

commission-intelligence

Explain sales commission calculations, resolve discrepancies, and model compensation scenarios for quota planning.

guia-matthieu/clawfu-skills · 19 tokens

pipeline-forecasting

Generate predictive pipeline forecasts with confidence intervals and scenario modeling for revenue planning.

guia-matthieu/clawfu-skills · 18 tokens

Audit PodClaw

Comprehensive audit of PodClaw — the autonomous agent system (Claude Agent SDK, Python). Use when asked to audit, review, or assess PodClaw — covering agent security, sandbox isolation, tool restrictions, budget limits, bridge API, and fail-closed patterns.

lroy-stack/ai-pod-store · 60 tokens