war-game

war-game is a command for Claude Code from ololand-ai/ololand-plugins. It costs 29 tokens per session (1,306 once invoked), scanned A, original, Apache-2.0.

A competitive strategy simulation for a business deal. It models several possible future scenarios, including changes in market share, pricing pressure, investment, and regulation over 16 quarters.

In plain words
What is it for?
It is used to simulate base-case, expansion, economic-stress, and regulatory-stress scenarios for an existing deal.
Why use it?
It helps compare how competitors and market conditions could affect a deal under different assumptions.

Command for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the ololand-dd plugin — 22 skills, 54 commands, 3 agents shipped together

Good fit It is used to simulate base-case, expansion, economic-stress, and regulatory-stress scenarios for an existing deal.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/ololand-ai/ololand-plugins/war-game
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/ololand-ai/ololand-plugins

Made for: Claude Code.

Or install ololand-dd, the plugin that ships this one along with the rest of its 22 skills, 54 commands, 3 agents.

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 war-game

README.md
[![agentmods](https://agentmods.dev/badge/commands/ololand-ai/ololand-plugins/war-game/github.svg)](https://agentmods.dev/commands/ololand-ai/ololand-plugins/war-game)
Your own site
<a href="https://agentmods.dev/commands/ololand-ai/ololand-plugins/war-game"><img src="https://agentmods.dev/badge/commands/ololand-ai/ololand-plugins/war-game/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 war-game

Your own site · 80×15
<a href="https://agentmods.dev/commands/ololand-ai/ololand-plugins/war-game"><img src="https://agentmods.dev/badge/commands/ololand-ai/ololand-plugins/war-game.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 29 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,306 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 $0.00029 $0.01306
Opus 5.5 $0.00012 $0.00522
Sonnet 5.5 $0.00006 $0.00261
Haiku 4.5 $0.00003 $0.00131

Measured 1mo ago against content hash 1b43e95f2adc, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

war-game 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 1mo 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/ololand-dd/commands/war-game.md · 61 lines

How it starts

The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.

War Game Simulation

Run an RL-powered competitive strategy simulation for a deal.

Usage

/war-game <deal_id> [scenarios]

Arguments

  • deal_id (optional) — The deal to simulate. If omitted, resolve it from the prose (see below).
  • scenarios (optional) — Comma-separated: base_case, expansion, macro_stress, regulated_stress, or all. Default: base_case. When the user asks about regulatory response, include regulated_stress.

Natural-language invocation (no deal_id)

Users rarely pass a bare deal_id — they describe a company and a counterfactual, e.g. "/war-game on Robinhood, assume it built Exchange Funds in-house instead of acquiring Frec/Cache. Competitive and regulatory response?" Treat the counterfactual as a caller-supplied hypothetical. If the simulator or required deal evidence is unavailable, relay that result; do not present an empty or inferred result as a simulation.

  1. Resolve the target to an existing deal. Use deal-search / list_deals to find an existing deal for the named company. If none exists, say that a deal context is required; do not create one automatically.
  2. Separate review from execution. For an audit, review, or read-only request, follow /plan: create or reuse the deal conversation session, submit the user's verbatim counterfactual with submit_plan_for_approval, render the plan, and stop for approval. After approval, direct the user to continue the same session in the OloLand app or normal SSE/message endpoint with the returned plan payload supplied as approved_plan on SubmitMessageRequest. That field supplies execution context; it is not a persisted or hash-validated approval identity. Do not call the MCP ask_deal_agent or talk_to_deal tools for this planned execution because they cannot carry the field; quoted plan prose is not a substitute. If the client cannot use the normal endpoint, report the governed review as unavailable on this rail; do not run a simulation or infer an answer. For a request that explicitly asks to run the simulation, continue to Execution step 1; that is a bounded, fixed-purpose tool call rather than a conversational executor turn.
  3. Pick scenarios from intent. "regulatory response" → regulated_stress; "across conditions" / unspecified depth → all; otherwise base_case.
  4. If the user supplied a custom counterfactual or premise that would change the simulated business, buyer, capability, market, or competitive setup, fail closed as unsupported on this MCP rail. run_war_game_simulation accepts only deal_id and scenarios; do not discard the premise, invent an argument, substitute another tool, or run the default deal-context simulation as if it answered the custom question. State that the requested premise cannot be carried by this bounded tool. A plain scenario request with no custom premise may continue to Execution.
  5. Separate factual buyer premises from simulator predictions. Do not claim a buyer/acquirer identity, observed strategy, historical action, expected synergy, or any other real-world premise unless a tenant-authorized returned source supports it with an inline citation. Keep caller-provided buyer premises labeled hypothetical. A completed simulator's modeled strategy, likely action, competitor response, EV distribution, or robustness score may be relayed without a document citation only when it is clearly labeled simulator prediction and tied to the exact returned simulation identity and scenario; never restate that prediction as a sourced fact.

Read the full file on GitHub · 61 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. 1mo ago First seen · 61 lines · 29 tokens per session scan A 1b43e95f2adc

Subscribe to this mod's changes

war-game is a command published in the GitHub repository ololand-ai/ololand-plugins (0 stars, last pushed 3d ago), licensed Apache-2.0. It adds 29 tokens to every session and 1,306 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.