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/deal-canvas)<a href="https://agentmods.dev/commands/ololand-ai/ololand-plugins/deal-canvas"><img src="https://agentmods.dev/badge/commands/ololand-ai/ololand-plugins/deal-canvas/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.
<a href="https://agentmods.dev/commands/ololand-ai/ololand-plugins/deal-canvas"><img src="https://agentmods.dev/badge/commands/ololand-ai/ololand-plugins/deal-canvas.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00031 | $0.01127 |
| Opus 5 | $0.00015 | $0.00563 |
| Sonnet 5 | $0.00006 | $0.00225 |
| Haiku 4.5 | $0.00003 | $0.00113 |
Grade A, and why
deal-canvas 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deal Canvas
Use this command when the user asks for a chart, graph, KPI summary, table, or infographic on the deal canvas — a persisted, dock-visible artifact, not a one-off markdown table in chat.
Usage
/deal-canvas <deal_id> chart <chart_type> "<title>" <x_axis_key> <series...>
/deal-canvas <deal_id> kpi "<title>" <items...>
/deal-canvas <deal_id> table "<title>" <columns...> <items...>
/deal-canvas <deal_id> infographic "<title>" <sections...>
/deal-canvas <deal_id> update <tile_id> <changed fields...>
The binding contract (applies to every kind)
Every numeric series, item, or column must be bound one of two ways — there is no free-text numeric value on this surface:
- Engine-bound —
{"mode": "engine", "metric": <engine metric>}and OloLand fills the value from its own engines (financial snapshot / DCF / LBO). Never setunit/scaleon an engine-bound value; they're ignored if present. - Cited —
{"mode": "cited", "citations": [{"document_id": <file in this deal>, "page": <n>}]}with the row values passed indata(charts) or inline on the item/column (KPI/table/infographic). Every cited series must carry at least one citation that resolves to a file in this deal, or the call is refused witherror_code="uncited_series". For KPI rows, tables, and infographics specifically, a cited entry also requires an explicitunit(usd|percent|ratio|count) and, whenunit="usd", an explicitscale(actual|thousands|millions|billions) — OloLand converts to canonical absolute USD before storing. Missing or invalid unit/scale is refused the same way, never defaulted.
Execution
- chart — call
mcp__ololand__create_deal_chart(deal_id, chart_type, title, x_axis_key, series, data, filters, insights).chart_typeis one ofline,bar,area,scatter,pie,composed.datacarries the rows for cited series only (ignored for engine series). Re-issuing an identical chart returns the existing tile (deduped: true) instead of minting a duplicate — don't apologize for or hide a dedupe response, just report the existing tile. - kpi / table / infographic — call
mcp__ololand__create_deal_artifact( deal_id, kind, title, items, columns, x_axis_key, data, sections, insights)withkindset tokpi_row,table, orinfographic. Usekind="infographic"with 1-12 orderedsectionsfor composite requests that combine several of the above. Never author raw HTML or sandbox files for this surface — the artifact system renders it. - update — for any follow-up like "make it a bar chart" or "add EBITDA
margin," call
mcp__ololand__update_deal_artifact(deal_id, tile_id, ...)with thetile_idthe create call returned, restating the full binding (series/items/columns/sections) — every value is re-verified against engines/citations exactly as on creation, so a partial restatement drops whatever isn't repeated. The prior spec is kept as a restorable version, so this is safe to iterate on.
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 · 83 lines · 31 tokens per session scan A 316ce4880b18
deal-canvas is a command published in the GitHub repository ololand-ai/ololand-plugins (0 stars, last pushed 4d ago), licensed Apache-2.0. It adds 31 tokens to every session and 1,127 once invoked, about $0.0002 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.
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