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.
npx skills add ololand-ai/ololand-plugins --skill cmd-ebitda-bridgegit 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/skills/ololand-ai/ololand-plugins/cmd-ebitda-bridge)<a href="https://agentmods.dev/skills/ololand-ai/ololand-plugins/cmd-ebitda-bridge"><img src="https://agentmods.dev/badge/skills/ololand-ai/ololand-plugins/cmd-ebitda-bridge.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 | $0.00065 | $0.00632 |
| Opus 5 | $0.00032 | $0.00316 |
| Sonnet 5 | $0.00013 | $0.00126 |
| Haiku 4.5 | $0.00006 | $0.00063 |
Grade A, and why
ololand-forensic-qoe-ebitda-bridge 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 3d 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codex wrapper for /ebitda-bridge
Follow the OloLand command instructions below when the user asks for /ebitda-bridge or the equivalent workflow in Codex.
EBITDA Bridge
Walks reported EBITDA to adjusted/normalized EBITDA, classifying every add-back. The classifier flags add-backs that look one-time but recur, pro-forma adjustments that lack supporting documentation, and any management add-back that doesn't survive scrutiny.
Usage
/ebitda-bridge <deal_id>
Arguments
deal_id(required) — The deal to analyze. Requires reported EBITDA + management's adjustment schedule + 2-3 years of historical financials for recurrence testing.
Execution
- Call
build_ebitda_bridge(deal_id)from the MCP server. If the user supplied explicit financial data, pass it asfinancial_data. Do not pass aprimitivesargument toanalyze_forensic_qoe; that tool runs the full deal-scoped battery. - The engine pulls the management EBITDA bridge from the data room (or extracts from CIM/QofE workbook).
- For each adjustment, the classifier evaluates:
- Recurrence — does this adjustment appear in 2+ of the last 3 years? (If yes, it's not one-time.)
- Documentation — is there supporting evidence for the dollar amount?
- Reasonableness — is the magnitude consistent with industry benchmarks?
- Returns the bridge with each adjustment tagged and a normalized EBITDA that excludes questionable add-backs.
Output
| Add-back | Mgmt $ | Classification | Normalized $ | Why |
|---|---|---|---|---|
| Owner comp normalization | 1,200K | accepted | 1,200K | sole-shareholder, replacement comp documented |
| "One-time" legal | 450K | recurring | 0K | also in FY23, FY22, FY21 |
| COVID add-back | 800K | questionable | 400K | Q2'21 only, no supporting invoices for 50% |
Plus a summary line: management EBITDA $X.XM → normalized EBITDA $Y.YM (delta $Z.ZM).
Why this matters
Inflated EBITDA is the #1 driver of overpaying in PE deals. The EBITDA bridge classifier is the single most important forensic test in QoE. Running it pre-LOI tells you whether the headline multiple you're solving for is even directionally right.
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.
- 3d ago First seen · 55 lines · 65 tokens per session scan A 746ab6df85b2
ololand-forensic-qoe-ebitda-bridge is a skill published in the GitHub repository ololand-ai/ololand-plugins (0 stars, last pushed 2d ago), licensed Apache-2.0. It adds 65 tokens to every session and 632 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 2026-09-03.
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