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.
git clone --depth 1 https://github.com/ololand-ai/ololand-pluginsWrote 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.
[](https://agentmods.dev/commands/ololand-ai/ololand-plugins/firm-playbook)<a href="https://agentmods.dev/commands/ololand-ai/ololand-plugins/firm-playbook"><img src="https://agentmods.dev/badge/commands/ololand-ai/ololand-plugins/firm-playbook.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00061 | $0.00598 |
| Opus 5 | $0.00030 | $0.00299 |
| Sonnet 5 | $0.00012 | $0.00120 |
| Haiku 4.5 | $0.00006 | $0.00060 |
Grade A, and why
firm-playbook 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/firm-playbook
You are reading THIS firm's standing investment configuration for the deal's tenant. The playbook encodes institutional preferences the firm has codified — they are more authoritative than market-default heuristics. When a playbook value constrains a number you're about to commit to (WACC, exit multiple, target IRR), honor it OR explicitly call out the deviation.
This is distinct from /playbook-recall, which surfaces patterns from past similar deals (cross-deal learning). /firm-playbook returns the firm's STANDING CONFIG.
Required inputs
- deal_id — the OloLand deal whose tenant's playbook to recall.
Action
Call mcp__ololand__recall_firm_playbook with the deal_id. Render the response in this format:
Firm playbook for <deal_id> (resolution: <deal_pin | tenant_default>)
Target criteria:
Industries: <list>
Geographies: <list>
Revenue range: $<min> – $<max>
Min EBITDA margin: <pct>
Min growth rate: <pct>
Valuation thresholds:
Max EV / Revenue: <x>
Max EV / EBITDA: <x>
Target IRR: <pct>
Min MOIC: <x>
Approval thresholds:
Partner: $<value>
IC: $<value>
Board: $<value>
Standard timelines:
Initial review: <days>
LOI → close: <days>
DD period: <days>
IC review: <days>
Preferred frameworks: <list>
Custom rules:
- <name>: <condition> [severity: <high | medium | low>]
Empty-playbook handling
If the response is playbook: null (no active playbook configured for this tenant), say so explicitly and recommend the user configure one via the dashboard. Do NOT fabricate a default playbook. Fall back to OloLand's market-default methodology for the deal in question.
Deviation discipline
If the user is about to commit to a number that conflicts with the playbook (e.g. WACC outside the firm's range, exit multiple above the firm's ceiling), surface the conflict before answering. Either:
- Adjust the number to fit the playbook range, OR
- Quote the playbook value and explain the deviation rationale
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.
- 8d ago First seen · 69 lines · 61 tokens per session scan A a01c5e54a06c
firm-playbook is a command published in the GitHub repository ololand-ai/ololand-plugins (0 stars, last pushed 3d ago), licensed Apache-2.0. It adds 61 tokens to every session and 598 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.
Other commands, from other repositories
valuation-methods
Valuation methods analysis — multiples, DCF inputs, PEG integration, valuation assumption extraction.
merit-reconcile
Preview or check the status of Stripe → Merit payout reconciliation (read-only).
audit-checklist
Perform an internal audit, review controls, or prepare for an external financial audit.
scan
Scan AWS account for cost optimization.
finops-status
Orientation — say where an opportunity or assignment sits in the five-step FinOps lifecycle and what unlocks next. Useful when a record has no active stage: an opportunity while its assignments do the work, an assignment whose plan has not been approved yet, or a rejected or archived assignment. Read-only; mutates…
audit
Scan for non-kernel money math. Rebuild critical flows as JournalEntrys. Replay and prove. Complements /ledger-verify.