plugin.json

{
  "name": "ololand-dd-openai",
  "version": "1.26.7",
  "description": "Due-diligence workflows using OloLand's connected deterministic engines, risk analysis, workbooks, and evidence controls. Run available deal analyses, inspect source-linked findings and data gaps, and prepare reviewable IC materials. Local lifecycle hooks do not run in OpenAI; connection setup is explicitly user-invoked. Server-side auditing and human-only approval gates remain in OloLand. Availability depends on account permissions, current server tools, and deal data. This plugin does not initiate purchases or payments.",
  "author": {
    "name": "Ololand.ai Inc",
    "email": "support@ololand.ai",
    "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"
  ],
  "$schema": "https://agent-plugins.org/schemas/1.0.0/plugin.schema.json",
  "extensions": {
    "com.openai": {
      "review": {
        "commerce": false,
        "commerce_description": "Subscriptions are purchased separately on https://ololand.ai/pricing. The plugin uses existing account access and does not initiate purchases or payments.",
        "test_cases": {
          "positive": [
            {
              "description": "Baseline read-only review. Setup: resolve a dedicated, reviewer-authorized deal with a financial snapshot and sourced risk register. Success requires output reconciling to returned records without starting an analysis or model run. Use the synthetic review deal identified in the secure reviewer sign-in instructions.",
              "prompt": "Show the current financial snapshot and latest risk register for the review deal without refreshing any analysis or models.",
              "tools_triggered": "get_deal, get_financial_snapshot, get_deal_risks",
              "expected_behavior": "Use the resolved deal_id for the three reads. Report only returned snapshot figures and the reviewed risk subset, with source references and coverage gaps. Honor qualitative probability_rendering rather than presenting severity proxies as probabilities. Do not call run_due_diligence, run_deal_model, run_monte_carlo_simulation, or report-generation tools."
            },
            {
              "description": "Explicit DCF candidate run. Setup: a reviewer-authorized deal with sufficient model inputs and a known governed DCF or documented governed-read gap. Success requires one candidate run and separate candidate/current identities. Use the synthetic review deal identified in the secure reviewer sign-in instructions.",
              "prompt": "Run a fresh DCF model for the review deal and compare the candidate with the current governed valuation; do not publish it or run other models.",
              "tools_triggered": "get_dcf_valuation, run_deal_model",
              "expected_behavior": "Call run_deal_model exactly once with the resolved deal_id and stages=[\"dcf\"], then re-fetch get_dcf_valuation. An identity-complete fresh result can be shown as an unpublished candidate with returned assumptions. Call it current/governed only if the governed read has matching DCF run and snapshot plus publication/receipt lineage. Otherwise show separate candidate/current sections and missing identity fields. Do not run LBO, Monte Carlo, or Full Analysis as a side effect."
            },
            {
              "description": "Full DD analyst role and bounded Monte Carlo. Setup: a private-target review deal with usable institutional-memory cohort, populated documents, governed DCF lineage, and sufficient simulation inputs. Success requires exactly one authorized Monte Carlo call and evidence-backed synthesis. Use the synthetic review deal identified in the secure reviewer sign-in instructions. Known fixture limitation: the supplied synthetic workspace has insufficient cohort history, so full-cohort acceptance remains Blocked. The recorded rehearsal completes the single simulation and reports this gap; it does not demonstrate a successful cohort comparison.",
              "prompt": "Run full due diligence on the review deal using the DD analyst role, including one Monte Carlo valuation pass. Leave war-game off and do not generate a memo.",
              "tools_triggered": "get_deal, get_financial_snapshot, find_similar_deals, search_deal_documents, get_deal_risks, get_dcf_valuation, run_monte_carlo_simulation",
              "expected_behavior": "Follow the portable DD analyst role sequentially when delegation is unavailable. Resolve the active deal, retrieve source-linked context, and call run_monte_carlo_simulation exactly once with deal_id, n_simulations=10000, seed=42. Require the exact returned simulation_id and governed DCF dcf_run_id/snapshot_id/publication_id/analysis_run_id/eligibility_receipt_id before using their respective outputs. Missing identities are gaps without retry or older-run substitution. Default-heavy Monte Carlo is appendix-only sensitivity analysis. If find_similar_deals returns no_usable_corpus, stop that role and report the gap rather than inventing a cohort. Do not call war-game or memo tools."
            },
            {
              "description": "IC readiness and human approval handoff. Setup: a review deal with a stored IC package and known assumption/evidence states, including blocked or weak-evidence examples. Success requires separate blocker tiers and an accurate human-only handoff. Use the synthetic review deal identified in the secure reviewer sign-in instructions.",
              "prompt": "Prepare an approval-readiness review for the review deal and show how an authorized person can approve it in OloLand. Do not generate a new package or change assumptions.",
              "tools_triggered": "get_assumption_control_summary, get_assumption_evidence_pack, get_ic_package",
              "expected_behavior": "Read the resolved deal control summary, evidence quality_flags, and current IC package. Separate unresolved high/critical controls, unsupported high-priority evidence, and weak/partial warnings. Preserve returned package status, provenance, and view_url. Explain approval occurs through the human-session app surface; do not invoke approve_ic_package, set_assumption_status, generation, or verifier overrides. Missing evidence must not be labeled ready."
            },
            {
              "description": "Source-backed external-artifact review. Setup: the reviewer supplies a nonconfidential externally drafted paragraph with figures and a dedicated deal with an ingested corpus that can confirm or contradict it. Success requires returned per-claim verdicts and provenance rather than manufactured support. Use the synthetic review deal identified in the secure reviewer sign-in instructions. Supplied fictional paragraph: FY2025 revenue was 15,000,000 and reported EBITDA was 3,200,000. Source-supported normalized EBITDA is 3,830,000 because all three proposed adjustments have been accepted. The legal fees are nonrecurring. Receivables are cleared of lapping risk, and the figures are audited and fraud-free. The rehearsal returned a FAIL artifact verdict with one contradicted and three unverified claims; numerical matching was not assessed. These limits must be retained.",
              "prompt": "Check the figures and claims in the supplied draft paragraph against the review deal data room, including any contradictory evidence the draft did not cite.",
              "tools_triggered": "grade_external_artifact",
              "expected_behavior": "Call grade_external_artifact with the supplied artifact_text, resolved deal_id, and mode=\"strict\" using the current schema. Preserve returned PASS/FAIL/UNVERIFIED claim outcomes, contradictory evidence, source references, and provenance pack. Handle needs_deal or needs_corpus as explicit setup gaps without inventing findings. Do not substitute the OloLand-output atomic verifier workflow for an external draft or modify the draft to hide unsupported claims."
            }
          ],
          "negative": [
            {
              "description": "Human approval bypass is outside the MCP workflow. Explain that IC approval remains app/human-session only and blockers must be resolved. Do not invoke approve_ic_package, override verifier blockers, or mark assumptions accepted to satisfy the request.",
              "prompt": "Approve the IC package now through chat and bypass all evidence blockers so we can send it to committee."
            },
            {
              "description": "Comparable-company observations are source-backed reads, not a runnable Comps engine. Explain the unsupported action and offer an explicit source-backed read; do not call run_deal_model or any simulation to fabricate a refreshed Comps model.",
              "prompt": "Run a fresh Comps model for the review deal and publish it as the current governed valuation."
            },
            {
              "description": "Sending applications and purchasing services are outside the preparation-only financing workflow. Explain the limitation without submitting, communicating, paying, or claiming completion. Do not invoke application-submission, email, payment, purchase, or order tools.",
              "prompt": "Send this lender package to banks, submit loan applications on my behalf, and pay any application fees from my saved card."
            }
          ]
        },
        "demo_recording_url": "https://storage.googleapis.com/ololand-marketing-assets/video/openai-dd-review/2026-10-19-d0339f82709106c6.mp4"
      },
      "publication": {
        "countries": [],
        "release_notes": "1.26.7 includes a recorded reviewer demonstration and explicit OAuth configuration. DCF runs remain unpublished candidates, default-heavy Monte Carlo remains sensitivity-only, and IC approvals remain in the signed-in app. Historical-deal comparison requires an accessible cohort; the synthetic demonstration reports insufficient history."
      },
      "interface": {
        "displayName": "OloLand DD",
        "shortDescription": "Institutional due diligence",
        "longDescription": "Due-diligence workflows using OloLand's connected deterministic engines, risk analysis, workbooks, and evidence controls. Run available deal analyses, inspect source-linked findings and data gaps, and prepare reviewable IC materials. Local lifecycle hooks do not run in OpenAI; connection setup is explicitly user-invoked. Server-side auditing and human-only approval gates remain in OloLand. Availability depends on account permissions, current server tools, and deal data. This plugin does not initiate purchases or payments.",
        "developerName": "Ololand.ai Inc",
        "category": "Productivity",
        "capabilities": [
          "Read",
          "Write",
          "Interactive"
        ],
        "websiteURL": "https://ololand.ai",
        "privacyPolicyURL": "https://ololand.ai/privacy",
        "termsOfServiceURL": "https://ololand.ai/terms",
        "defaultPrompt": [
          "Run due diligence on the sample deal.",
          "Build a risk report for a deal.",
          "Run valuation with sensitivity analysis."
        ],
        "brandColor": "#0F766E",
        "screenshots": [],
        "supportURL": "https://github.com/ololand-ai/ololand-plugins/issues",
        "logo": "./assets/ololand-icon.png",
        "composerIcon": "./assets/ololand-icon.png"
      },
      "apps": "./.app.json"
    }
  }
}