Update to OloLand DD

{
  "description": "Use when the user asks to run the OloLand ololand-dd-precedents workflow. Search ~61K public M&A transactions (2006-2026) for precedent deals and market context — outcome-labeled, with SEC filing citations.",
  "included_files": [
    {
      "relative_path": "agents/openai.yaml",
      "size_in_bytes": 448
    }
  ],
  "name": "ololand-dd-precedents",
  "skill_md_contents": "---\nname: ololand-dd-precedents\ndescription: \"Use when the user asks to run the OloLand ololand-dd-precedents workflow.\\\n  \\ Search ~61K public M&A transactions (2006-2026) for precedent deals and market\\\n  \\ context \\u2014 outcome-labeled, with SEC filing citations.\"\n---\n\n\n# Workflow for ololand-dd-precedents\n\nFollow the OloLand command instructions below when the user asks for `ololand-dd-precedents` or the equivalent workflow.\n\n# Precedent Deals\n\nSearch OloLand's public M&A corpus for market context and precedent transactions — \"who has bought companies like this, when, and roughly for how much\".\n\n## Usage\n\n```\nololand-dd-precedents <query> [min_ev=$M] [max_ev=$M] [from=YYYY] [to=YYYY] [outcome=completed|terminated] [sector=...]\n```\n\n## Arguments\n\n- `query` (optional) — free text matched against deal summaries and company names.\n- `min_ev` / `max_ev` (optional) — enterprise-value band, in millions.\n- `from` / `to` (optional) — announcement-year range.\n- `outcome` (optional) — `completed` or `terminated`. Omit for any/unresolved.\n- `sector` (optional) — one SEC SIC division: `agriculture`, `mining`, `construction`, `manufacturing`, `transport_utilities`, `wholesale`, `retail`, `finance_insurance_real_estate`, `services`, `public_administration`.\n\n## Execution\n\n1. Call `search_precedent_deals` with the mapped arguments. Cap `limit` at 25; if the user wants a specific ordinal offset for citations across a multi-step research turn, pass `citation_start_number` accordingly (shared counter with `search_deal_documents`).\n2. **This is PUBLIC filing data covering the whole market — not this firm's own deals.** If the user actually means the firm's pipeline (\"our deals like this one\"), use `ololand-dd-similar-deals` or `compare_deals_by_attribute` instead; do not silently redirect without saying so.\n3. **Read the returned `corpus_coverage` note before drawing any conclusion from an empty result or a null field.** A `NULL` premium, target financial, or multiple means \"not disclosed in the source filing,\" never \"zero.\" Outcome and close data are still being backfilled — a missing `outcome` means unresolved, not that the deal failed to close.\n4. Do not assert a sector or period has no comparable deals from an empty page alone; report what the query found and what the corpus note says about coverage.\n\n## Citing\n\nEvery deal with a source filing carries a `citation_number` — use it for claims about the transaction itself (parties, dates, outcome). For a PREMIUM, MULTIPLE, or TARGET FINANCIAL specifically, cite `valuation_citation_numbers[<field>]` instead — it numbers the exact filing URL substantiating that value, which is often a different filing from `citation_number`. Both live in one `[N]` namespace. A value absent from `valuation_citation_numbers`, or a deal with no `citation_number`, has no openable source — do not attach a bracket-number marker to it.\n\n## Output\n\nReport a table: Company | Acquirer | Announced | Sector | EV ($M, cited) | Premium (cited, or \"not disclosed\") | Outcome | `[N]`.\n\nFollow with the `corpus_coverage` note verbatim (or a faithful summary of it), then a one-line takeaway on what this precedent set implies for the deal at hand.\n\n## After Completion\n\nIf the user is evaluating a specific deal, suggest `ololand-dd-valuation <deal_id> read all` to compare the precedent range with governed DCF/LBO and source-backed Comps without starting a model run.\n\n\n## OpenAI execution requirements\n\nUse the connected MCP server's current tool schemas. Do not invent tool arguments, job-status endpoints, inputs, or outputs. If a referenced tool is unavailable, explain the limitation and request the needed connection or data. Invoke writes only when the user has requested the corresponding action. Do not initiate purchases or payments. An unrun, unsupported, or unavailable procedure is a gap, never a passing result.\n\n\nOpenAI cannot execute local lifecycle hooks. Use the packaged explicit setup/review workflow when requested. Server-side MCP auditing remains authoritative; preserve evidence blockers and human-only approval gates.\n\nClaim-correction submission is unsupported in this OpenAI upload because the current handler records surface=cowork. Do not invoke submit_agent_claim_correction from OpenAI. Explain the limitation and retain proposed correction text for human review without claiming submission. See unsupported-workflows.json for the excluded canonical workflow.\n"
}