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.
/plugin marketplace add ololand-ai/ololand-pluginsnpx agentmods add plugins/ololand-ai/ololand-plugins/ololand-ddgit clone --depth 1 https://github.com/ololand-ai/ololand-pluginsGrade A, and why
ololand-dd 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 2d 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.
What it actually says
{
"name": "ololand-dd",
"version": "1.24.2",
"description": "Institutional due diligence for Claude — deterministic DCF / LBO / Monte Carlo / Real Options engines, 311-factor risk taxonomy (67 diligence categories) with SaaS / healthcare / real-estate / industrial overlays, forensic QoE primitives, cross-document reconciliation (CPA > tax > management > AI), MaskablePPO war-game simulation, assumption controls that gate IC approval, analytical workbench tools for QoE/compliance/scenarios/earnings, value-impact ledger reads, deal-health actions, workbooks with template-driven population, acquisition-financing prep (deterministic analysis, provider-sourcing prep, lender pre-reads), company discovery, watchlists, IC-package lifecycle dispatch, advisory requests, external-artifact grading (the Cowork adoption funnel) and cross-document conflict detection, verified forensic screen marketplace support, and a regulator-grade audit trail with replay and compliance-framework exports. Three sub-agents (dd-analyst, forensic-screener, war-game-strategist) plus a flywheel that retrains from analyst corrections. Counter-positions Anthropic's native private-equity plugin.",
"author": {
"name": "OloLand",
"email": "[email protected]",
"url": "https://ololand.ai"
},
"homepage": "https://ololand.ai",
"repository": "https://github.com/ololand-ai/ololand-plugins",
"license": "Apache-2.0",
"keywords": [
"finance",
"private-equity",
"due-diligence",
"m-and-a",
"valuation",
"lbo",
"dcf",
"risk-analysis",
"forensic-qoe"
]
}
What it installs
The manifest is a name and a version. 47 commands, 3 agents travel with it, and installing the plugin installs all of them — 2,127 tokens a session between them. Each is measured on its own page, and each can be installed alone.
- Command pre-screen A 51 tokens
- Command ic-memo-skeptical A 60 tokens
- Command valuation A 24 tokens
- Command record-outcome A 65 tokens
- Command firm-calibration A 36 tokens
- Command managed-agent A 114 tokens
- Command record-decision A 48 tokens
- Command source A 19 tokens
- Command assumption-controls A 30 tokens
- Command dd-analyze A 48 tokens
- Command deal-canvas A 31 tokens
- Command financing A 33 tokens
- Command ic-approve-readiness A 37 tokens
- Command meeting-prep A 34 tokens
- Command plan A 50 tokens
- Command risk-report A 33 tokens
- Command calibrate-vs-history A 47 tokens
- Command deal-search A 44 tokens
- Command inspect-run A 63 tokens
- Command playbook-recall A 37 tokens
- Command precedents A 31 tokens
- Command regulator-export A 50 tokens
- Command replay-run A 64 tokens
- Command similar-deals A 34 tokens
- Command talk-to-deal A 25 tokens
- Command ai-finserv-moves A 50 tokens
- Command firm-playbook A 61 tokens
- Command qoe-analysis A 48 tokens
- Command recall A 48 tokens
- Command unit-economics A 29 tokens
- Command value-impact A 34 tokens
- Command company-discovery A 26 tokens
- Command compliance-analysis A 33 tokens
- Command dd-merger-readiness A 23 tokens
- Command earnings-analysis A 23 tokens
- Command ic-package A 21 tokens
- Command scenario-analysis A 25 tokens
- Command deal-health A 23 tokens
- Command managed-context-agent A 24 tokens
- Command advisory A 12 tokens
- Command okf-export A 18 tokens
- Command dd-merger-analyze A 57 tokens
- Command dd-merger-rerun-math A 32 tokens
- Command remember A 54 tokens
- Command dd-correct A 50 tokens
- Command risk-matrix A 19 tokens
- Command new-deal B 71 tokens
- Agent dd-analyst A 57 tokens
- Agent war-game-strategist A 81 tokens
- Agent forensic-screener A 100 tokens
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.
- 2d ago First seen · 25 lines scan A 8b6924edf27f
ololand-dd is a plugin published in the GitHub repository ololand-ai/ololand-plugins (0 stars, last pushed 5d ago), licensed Apache-2.0. Its token cost is not measured: this kind of file is read by the harness, not the model. 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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