record-outcome

record-outcome is a command for Claude Code from ololand-ai/ololand-plugins. It costs 65 tokens per session (2,074 once invoked), scanned A, original, Apache-2.0.

A command that records a deal's original predictions and later compares them with realised results such as exit enterprise value, IRR, and MOIC. IRR is the annualised return, while MOIC is the return relative to the invested amount.

In plain words
What is it for?
Use it during underwriting to save predictions, or after at least 12 months post-close to enter realised results and score the predictions.
Why use it?
It preserves what was forecast and measures accuracy after the deal has enough post-close data, instead of losing that information when the session ends.

Command for Claude Code

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

Part of the ololand-dd plugin — 22 skills, 52 commands, 3 agents shipped together

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.

agentmods
npx agentmods add commands/ololand-ai/ololand-plugins/record-outcome
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, 52 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 record-outcome

README.md
[![agentmods](https://agentmods.dev/badge/commands/ololand-ai/ololand-plugins/record-outcome.svg)](https://agentmods.dev/commands/ololand-ai/ololand-plugins/record-outcome)
Your own site
<a href="https://agentmods.dev/commands/ololand-ai/ololand-plugins/record-outcome"><img src="https://agentmods.dev/badge/commands/ololand-ai/ololand-plugins/record-outcome.svg" alt="Measured on agentmods" height="20"></a>
Per session 65 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,074 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00065 $0.02074
Opus 5 $0.00032 $0.01037
Sonnet 5 $0.00013 $0.00415
Haiku 4.5 $0.00006 $0.00207

Measured 5d ago against content hash 59635c90bbad, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

record-outcome 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/ololand-dd/commands/record-outcome.md · 86 lines

How it starts

The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Record Outcome

Most AI tools forget every deal the moment the session ends. OloLand's flywheel does the opposite: it captures what the model predicted, then — once the deal closes and 12+ months of realized data exist — scores those predictions against reality. That accuracy history is what lets /calibrate-vs-history say "your firm overestimates revenue growth by 7pp in deals like this."

That read side only works if the write side is fed. This command is the write side. It does two things:

  1. Mints predictions (if the deal doesn't have them yet) by running the deterministic engines and a forecast run — so there is something concrete to grade later.
  2. Records realized actuals and closes the loop — stamping an accuracy score on each enterprise_value / irr / moic prediction.

Usage

/record-outcome <deal_id>

Two distinct moments call for it:

  • At underwriting / IC — mint the predictions so the deal is on the books to be graded later. (Steps 1-3 below; skip the actuals.)
  • Post-close (12+ months out) — record the realized exit and close the loop. (Steps 4-5 below.)

Arguments

  • <deal_id> (required) — the deal to mint predictions for and/or record actuals against.

Execution

The instructions below are for the model executing this command.

Decide the path first — and run only one. This command has two mutually exclusive paths: A. mint predictions (IC / underwriting time) and B. record actuals (post-close). Work out which moment the user is in and run only that path. Never run A then B in the same pass.

Why (look-ahead guardrail — this is load-bearing): a prediction is only meaningful if it was made before the outcome was known. If you mint a forecast at post-close — from a snapshot that already reflects how the deal turned out — and then score it against the known actuals, you fabricate an artificially-accurate "IC-time" prediction and poison the calibration / similar-deal corpus that /calibrate-vs-history depends on. So: only mint (A) when the outcome is genuinely unknown. In the post-close path (B) you do not mint — if no IC-time predictions exist, that deal simply doesn't get a graded score, and that is the correct, honest result (see step 5). Note that record_deal_actuals may return a backend hint like "run create_forecast_run first" when 0 predictions close — do not follow that hint post-close; it is only valid at IC time.

Read the full file on GitHub · 86 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 First seen · 86 lines · 65 tokens per session scan A 59635c90bbad

Subscribe to this mod's changes

record-outcome is a command published in the GitHub repository ololand-ai/ololand-plugins (0 stars, last pushed yesterday), licensed Apache-2.0. It adds 65 tokens to every session and 2,074 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 2026-08-31.