Update to OloLand DD

{
  "description": "Use when the user asks to run the OloLand ololand-dd-workbook workflow. List, read, create, or template-populate deal-scoped OloLand workbooks for analysis handoff.",
  "included_files": [
    {
      "relative_path": "agents/openai.yaml",
      "size_in_bytes": 397
    }
  ],
  "name": "ololand-dd-workbook",
  "skill_md_contents": "---\nname: ololand-dd-workbook\ndescription: Use when the user asks to run the OloLand ololand-dd-workbook workflow.\n  List, read, create, or template-populate deal-scoped OloLand workbooks for analysis\n  handoff.\n---\n\n\n# Workflow for ololand-dd-workbook\n\nFollow the OloLand command instructions below when the user asks for `ololand-dd-workbook` or the equivalent workflow.\n\n# Workbook\n\nUse this command when the user wants to see analysis workbooks, open workbook cells, create a workbook shell for follow-up analysis, or populate a workbook from a registered Excel template.\n\n## Usage\n\n```\nololand-dd-workbook list <deal_id>\nololand-dd-workbook get <workbook_id>\nololand-dd-workbook create <deal_id> \"QoE follow-up model\"\nololand-dd-workbook templates [profile_id]                 # registered template profiles, or one profile's mappings\nololand-dd-workbook generate <deal_id> <template_id> [extraction_id]  # DRAFT populated workbook from a template\nololand-dd-workbook excel-model <deal_id> [title]           # persisted/downloadable live-formula LBO model\nololand-dd-workbook extraction <deal_id> <document_id>     # extract canonical indicators from a deal document\nololand-dd-workbook extraction <extraction_id>             # read back a finished extraction\n```\n\n## Execution\n\n1. `list` — call `list_deal_workbooks(deal_id)`.\n2. `get` — call `get_workbook(workbook_id, include_cells=true)`.\n3. `create` — confirm title and description, then call `create_deal_workbook`.\n4. `templates` — call `list_excel_templates()` for the company's registered template profiles; for one profile's status and learned field mappings, call `get_template_profile(profile_id)`.\n5. `generate` — call `generate_populated_workbook(deal_id, template_id)`, optionally with an `extraction_id`. Returns a `task_id`; poll `check_task_status` for the audit manifest and any fields still needing confirmation.\n6. `excel-model` — call `generate_excel_model(deal_id, model_type=\"lbo\", title=title)` directly. This is distinct from the template-population path: it runs or reuses the persisted deterministic LBO engine, builds a live-formula `.xlsx`, saves it as a deal artifact, and returns the dock-artifact reference that opens with a Download button. `model_type=\"dcf\"` fails closed with `model_type_not_ready`; DCF workbook generation is not ready.\n7. `extraction` — call `extract_indicators_from_document(deal_id, document_id)` to extract canonical financial indicators (with cell-level citations) from an uploaded document; returns a `task_id`. Poll `check_task_status(task_id)` until it completes and reports the `extraction_id`, then read results with `get_canonical_extraction(extraction_id)`. If the user already has an extraction id, skip straight to the read.\n8. If the user wants to write model cells, explain that workbook cell authoring remains in the app/workbook surface unless a specific MCP cell-write tool exists.\n\n## Output\n\n- **Workbook list**: title, id, archived state, updated time.\n- **Workbook detail**: title, description, cells by position/type/title, execution errors.\n- **Create result**: workbook id and returned `view_url`.\n- **Templates**: profile id, name, status, mapped-field count.\n- **Generate result**: task id, then — from task status — the audit manifest and the list of fields needing human confirmation. Label the workbook DRAFT.\n- **Excel-model result**: artifact id, title, model type, file size, and returned dock-artifact reference. The workbook is persisted and downloadable; state that DCF workbook generation is not ready.\n- **Extraction**: extraction id, classified fields with citation coverage.\n\n## Guardrails\n\n- Do not invent workbook cells from chat. Create a shell and point the user to the app if cell-level authoring is needed.\n- **Template-populated workbooks are always DRAFT.** Only a human, via the in-app review UI, can finalize one — never present a generated workbook as finalized, and surface the fields the audit manifest says still need confirmation.\n- The `excel-model` workflow is engine-bound and separate from template review. Do not relabel it as a template-populated DRAFT or route it through `generate_populated_workbook`.\n- Keep analysis claims cited to documents or extracted knowledge; workbook presence alone is not evidence.\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"
}