Prompt Library

Company Fact Sheet.

Nine production prompts that compose a structured, AI-assembled company fact sheet from a private RAG engine over the firm's document store. Eight section drafters (Business, Product, Customers / GTM, Market, Competition, Unit Economics, Leadership, Supply Chain) each fan out 4–7 scoped sub-queries and synthesize one bulleted section, then a final 'Questions' prompt reads the assembled fact sheet and the partners' open questions to produce exactly five sharp diligence questions. This is raw research synthesis — not a partner-vetted IC brief or memo. It feeds the PMB, ICB, and ICM generators but is distinct from them.

Diligence

9 prompts

P.1

Where this runs

Playbook

02 · Diligence

Used by

Orchestrate full AI company fact sheet generation →

P.2

Prompts by section

The full set, in execution order. Each section is its own LLM call — cheaper to debug, easier to swap, and resilient against any single prompt failing. Templated fields like {{1__parent_record_values__name[]value}} are substituted at runtime by the orchestrator from CRM trigger data.

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Where this runs

Prompts by section

01 · gpt-5.2Business Description / HistorySection drafter — fans out 4–7 scoped RAG queries against the internal corpus, then synthesizes them into one bulleted fact sheet section.

02 · gpt-5.2Product(s) OverviewSection drafter — fans out 4–7 scoped RAG queries against the internal corpus, then synthesizes them into one bulleted fact sheet section.

03 · gpt-5.2Customers / GTMSection drafter — fans out 4–7 scoped RAG queries against the internal corpus, then synthesizes them into one bulleted fact sheet section.

04 · gpt-5.2Market SizeSection drafter — fans out 4–7 scoped RAG queries against the internal corpus, then synthesizes them into one bulleted fact sheet section.

05 · gpt-5.2Competitive LandscapeSection drafter — fans out 4–7 scoped RAG queries against the internal corpus, then synthesizes them into one bulleted fact sheet section.

06 · gpt-5.2Unit Economics / Financial ProfileSection drafter — fans out 4–7 scoped RAG queries against the internal corpus, then synthesizes them into one bulleted fact sheet section.

07 · gpt-5.2LeadershipPeople drafter — one bullet per person, top 3–4 team members, grounded in scraped public bios + the RAG corpus.

08 · gpt-5.2Supply Chain / ManufacturingSection drafter — fans out 4–7 scoped RAG queries against the internal corpus, then synthesizes them into one bulleted fact sheet section.

09 · gpt-5.2QuestionsFinal synthesizer — reads the assembled fact sheet (all 8 prior sections) plus the partners' open questions and writes exactly 5 sharp diligence questions.