research-company

name	research-company
description	Emit a thin org-brief YAML profiling a target organisation — the company-specific overlay that pairs with an industry primer to drive a digital-clone-grade substrate fork. The brief captures only what the vertical can't infer: identity, ownership, size, geography, ~10 subsidiaries, the named ELT, 3–5 strategic themes, and any stack overrides the company publicly disclosed. Function tree, regulator set, entity kinds, proposed-domain library, rituals, KPIs all come from the matching industry primer. Four-phase procedure; claims carry confidence + sources[]; gaps go in uncertainties[], never invented. USE FOR: profile a company before a customer pilot, generate an org-brief, prepare a customer-flavoured demo fork. DO NOT USE FOR: single-process design (use threadlight-design), pitch-deck authoring, code generation, exhaustive personae harvest (compose-org expands archetypes via faker at fork time).
metadata	{"version":"2.0.1"}

research-company

Profile an organisation from public web sources and produce a thin org-brief YAML — the company-specific facts that an industry primer can't infer.

Mental model

  industry primer        +        org brief         =     fork inputs
  (vertical canon)                (this skill)            (compose-org reads both)
  ───────────────────────         ──────────────────
  • function tree                 • identity (name, brand voice)
  • regulator catalogue           • ownership + size + geo
  • entity-kind set               • ~10 subsidiaries
  • 25+ proposed-domain library   • ~10 named ELT leaders
  • stack vendor candidates       • 3–5 strategic themes
  • rituals + KPI cinematics      • stack overrides (when public)
                                  • narrative-arc seeds (recent press)

If a vertical primer exists in references/industry-primers/, the research run is thin — 30–45 minutes of web work, ~300–500 lines of YAML. If no primer exists, write one first (see industry-primers/README.md) and graduate it before producing a brief.

When to use

• Profile a target organisation before a customer pilot or workshop
• Spin up a customer-flavoured demo fork
• Produce a reviewable spec a customer SME can sanity-check

Output convention

briefs/<slug>-org-brief.yaml

where <slug> is the kebab-case form of the target's short name (≤ 16 chars). briefs/ is gitignored — per-engagement output stays out of the public skill catalog. See AGENTS.md § 2.1 — Skills are agnostic.

Tooling priority

For every factual claim, point at one or more rows in sources[], gathered via:

1. web_fetch against the target's own properties — /about, /leadership, latest annual report or capital-markets-day PDF, /press or /newsroom, /governance. Self-reported data is confidence: medium unless cross-corroborated.
2. web_search for cross-corroboration — two independent secondary sources concurring lifts to confidence: high.
3. web_fetch against authoritative third parties — Wikipedia, national company registry (Companies House / SEC EDGAR / etc.), regulator filings, news of record.
4. web_search for stack-override signal — vendor case studies where the target's logo appears, recent partnership press ("Company X selects Vendor Y for …").

Never rely on a single answer-engine summary.

Output schema

The output conforms to references/brief-schema.md. The schema is deliberately thin — only the company-specific sections are required. Industry-standard sections (functions, entity kinds, proposed domains, regulators, rituals, KPIs) are optional in the brief; compose-org reads them from the primer when absent.

Key rules:

• Every Fact requires {value, confidence, source_refs?, notes?}.
• Every Source row needs {id, url, accessed, kind, used_for}.
• Truly-missing fields go in uncertainties[].
• meta.status walks in_progress → needs_review → ready.

The four phases

Phase 0 — Bootstrap

Create briefs/<slug>-org-brief.yaml with skeleton keys + empty arrays. Pick the matching primer; if none exists, stop and write one first.

Phase A — Identity, ownership, size, geography (10 min)

Sources: Wikipedia + /about + last annual report. Fill:

• identity.{name, short_name, slug, domain, description, brand_voice, industry, sub_industry, tagline}
• ownership.{structure, parent, ticker, founded, key_shareholders}
• size.{employees, revenue_usd, revenue_currency, revenue_period, customers_count, assets_count} — assets_count is the vertical-native scale signal (on-net buildings for telco; aircraft for airline; dealers for OEM)
• geo.{hq, regions, countries_present, key_hubs, footprint_notes}

Phase B — Subsidiaries + leadership (15 min)

• subsidiaries[]: walk the national registry. Cap at 15 — holding

  • materially-sized opcos. Each {id, name, country, role, regulator (reference the primer's regulator id), confidence}.

• leadership[]: just the publicly-named ELT from /leadership, typically 8–15 rows. Map each to a canonical persona role from the primer where one fits (ceo, cfo, coo, cpo, gc, dpo, cdo …); free-form for vertical-specific titles (e.g. chief_ai_officer). No LinkedIn-stalking for sub-ELT depth — the primer's archetype tree fills levels 3–6 at fork time.

Phase C — Strategic themes + stack overrides (10 min)

• strategic_themes[]: 3–5 themes drawn from the last 24 months of press releases + the most recent annual report's CEO letter. Each row gets a one-paragraph value, a function_focus[] (ids from the primer's function tree), a timeline_hint, and cites one or more press releases. These seed narrative_arcs.py and cadenced_rituals.py overrides at fork time.

• stack_overrides[]: ONLY systems the company has publicly disclosed (in press releases, joint vendor case studies, or earnings calls). Examples: "Company X selected Amdocs for OSS", "Company X built an agentic AI engine with Microsoft". Don't list inferred systems — those come from the primer's stack-candidate table at fork time.

Phase D — Cross-check & finalise (5–10 min)

Pick three confidence: high claims at random. Re-run web_search and confirm. Downgrade any that don't recheck.

Validate against the schema:

• Required sections (meta, identity, ownership, size, geo, sources) all populated.
• Every Fact has confidence.
• Every source_refs[] entry exists in sources[].
• meta.status → needs_review.

Print a short summary:

• counts: subsidiaries N, leadership N, strategic_themes N, stack_overrides N, sources N
• 3 highest-confidence claims
• 3 most material uncertainties
• one-line compose-org invocation hint

Wait for operator sign-off before flipping meta.status to ready.

Output budget

A thin org-brief lands at 300–500 lines of YAML. Anything > 800 suggests you're harvesting things the primer already covers — stop and trim. The breadth lives in the primer; the brief is the overlay.

Iterating the skill

When a generated brief looks wrong, fix this SKILL.md or the matching primer, not the brief. Two runs against the same target should diff to nothing meaningful except accessed dates.

Downstream re-use

Once meta.status: ready, hand off to compose-org (sibling skill, to be authored). That skill reads the brief + the matching primer and forks a target substrate repo into a customer-flavoured clone. The brief provides company facts; the primer provides vertical breadth. Together they drive the fork.