company-deep-dive

What this skill does

# Company Deep Dive

360° company research powered by Nimble's web data APIs.

User request: $ARGUMENTS

**Before running any commands**, read `references/nimble-playbook.md` for Claude Code
constraints (no shell state, no `&`/`wait`, sub-agent permissions, communication style).

---

## Instructions

### Step 0: Preflight

Follow the transport selection + standard preflight from `references/nimble-playbook.md` — pick CLI or MCP at session start, then run the standard preflight calls (date calc, today, profile, memory index) in parallel.

From the results:
- CLI missing or API key unset → `references/profile-and-onboarding.md`, stop
- Tag all `nimble` CLI calls: `nimble --client-source skill-company-deep-dive <subcommand>`. MCP path: not yet supported — see `references/nimble-playbook.md` for status.
- Profile exists → note it for context (company name helps frame the research). Read
  `~/.nimble/memory/companies/index.md` to check if the target company already has
  prior research. Follow `[[path/entity]]` cross-references to load related context.
  - **Prior research exists:** Load it. Run in **refresh mode** — focus on what's new
    since the last report date. Tell the user: "I have prior research on [Company]
    from [date]. Refreshing with latest data."
  - **No prior research:** Run in **full mode** — comprehensive across all dimensions.
- No profile → that's fine. Company deep dive doesn't require onboarding (unlike
  competitor-intel). Proceed directly to Step 1.

### Step 1: Identify Target Company

Parse the target company from `$ARGUMENTS` or the user's message.

**If clear** (e.g., "research Stripe", "tell me about Datadog"):
- Extract the company name
- Run two Bash calls simultaneously to confirm identity:
  - `nimble search --query "[Company] official site" --max-results 3 --search-depth lite`
  - `nimble search --query "[Company] company overview" --max-results 5 --search-depth lite`
- Confirm briefly: "Researching **[Company]** ([domain])..."

**If ambiguous** (e.g., "research Mercury" — could be bank, auto, or other):
- Ask one clarifying question with the top candidates

**If missing** — ask: "Which company would you like me to research?"

**Scope selection** — if the user hasn't specified depth, default to **full deep dive**.
If they say "quick overview", "brief", or "summary", run a **quick mode** that skips
the Deep Extraction step and produces a shorter report.

### Step 2: WSA Discovery

Discover available WSAs for the target company's domain. Run both searches
simultaneously:

```bash
nimble agent list --search "{company-domain}" --limit 20
```

```bash
nimble agent list --search "{company-name}" --limit 20
```

From the results, filter for WSAs with `entity_type` matching SERP or PDP, and
prefer `managed_by: "nimble"`. Validate each with
`nimble agent get --template-name {name}`, then cache discovered WSA names + params
for the run. Pass them to dimension agents in Step 3 for enrichment alongside
`nimble search`. If no WSAs found, continue with `nimble search` alone.

### Step 3: Parallel Research Across Dimensions (sub-agents)

Read `references/dimension-agent-prompt.md` for the full agent prompt template.
Follow the sub-agent spawning rules from `references/nimble-playbook.md`
(bypassPermissions, batch max 4, explicit Bash instruction, fallback on failure).

Spawn `nimble-researcher` agents (`agents/nimble-researcher.md`) with
`mode: "bypassPermissions"`. Each agent researches one dimension of the company.
Pass discovered WSA names from Step 2 to each agent so they can use them for
enrichment alongside `nimble search`.

**Important:** The Nimble API has a 10 req/sec rate limit per API key. With each agent
running 4-5 searches in parallel, limit concurrent agents to 2 per batch to stay under
the limit. Run overview searches in their own phase, not alongside agent batches.

**Call estimation & Scaled Execution:** Before launching agents, estimate total API
calls: 2 overview searches + ~5 searches per agent × 5 agents = ~27 calls. Each agent
should use `extract-batch` or `agent run-batch` for 11+ calls instead of individual
calls. See the Scaled Execution pattern in `references/nimble-playbook.md` for tier
selection.

**Phase A — Overview searches** (run directly, before agents):

- `nimble search --query "about" --include-domain '["[domain]"]' --max-results 3 --search-depth lite`
- `nimble search --query "[Company] Wikipedia OR Crunchbase OR Pitchbook" --max-results 5 --search-depth lite`

These give foundational context (founding date, HQ, employee count, mission) that
frames all dimensional findings.

**Phase B — Batch 1** (2 agents simultaneously):

| Agent | Dimension | Focus |
|-------|-----------|-------|
| 1 | **Funding & Financials** | Funding rounds, valuation, revenue signals, investors, financial health |
| 2 | **Product & Technology** | Products, tech stack, recent launches, engineering blog, open-source |

**Phase C — Batch 2** (2 agents simultaneously):

| Agent | Dimension | Focus |
|-------|-----------|-------|
| 3 | **Leadership & Team** | Founders, C-suite, key hires, departures, team size, culture signals |
| 4 | **Recent News & Events** | Press coverage, announcements, partnerships, awards, conferences |

**Phase D — Batch 3** (1 agent):

| Agent | Dimension | Focus |
|-------|-----------|-------|
| 5 | **Market Position** | Competitors, market share, positioning, analyst coverage, customer reviews |

**Refresh mode adjustment:** If prior research exists, pass the known facts to each
agent as context so they focus on what's new. Agents should use `--start-date` to
filter for recent data only.

**Fallback:** If any agent fails or returns empty, run those dimension searches
directly from the main context. Don't leave gaps in the report.

### Step 4: Deep Extraction

From all agents' results, identify the **top 5-8 most informative URLs** across
dimensions. Prioritize:
- Funding announcements with specific amounts
- Official product/feature pages
- Executive interviews, podcast appearances, or conference talks
- In-depth analyst or journalist profiles
- The company's own about/team page

Make one Bash call per URL, all simultaneously:

`nimble extract --url "https://..." --format markdown`

For extraction failures, follow the fallback in `references/nimble-playbook.md`.

**Quick mode:** Skip this step entirely. Report from search snippets only.

**WSA enrichment:** If WSAs were discovered in Step 2, use them here for richer
extraction on key URLs before falling back to `nimble extract`.

### Step 5: Synthesize Report

Structure the output as a **360° Company Report**:

```
# [Company Name] — Deep Dive
*As of [today's date]*

## Quick Assessment
[2-3 sentence verdict: what this company is, where they stand, and the one thing
that matters most right now. This is the "if you read nothing else" paragraph.]

## Company Overview
- Founded: [year] | HQ: [location] | Employees: [estimate]
- Domain: [domain] | Industry: [industry]
- Mission/focus: [one line]

## Funding & Financials
[Latest round, total raised, key investors, valuation signals, revenue indicators.
Every claim dated and sourced.]

## Leadership & Team
[Founders, C-suite, notable recent hires or departures. Executive perspectives
on company direction — direct quotes when available from interviews or talks.]

## Product & Technology
[Core products, recent launches, tech stack signals, engineering culture,
open-source contributions. What they're building and how.]

## Market Position
[Key competitors, differentiation, market share signals, analyst perspectives,
customer sentiment from reviews (G2/Capterra/Reddit).]

## Recent News & Events
[Chronological, most recent first. Each entry dated with source.]

## Strategic Outlook
[Synthesis across all dimensions: where the company is heading, key risks,
growth signals, and strategic bets. This is insight, not summary.]

## Sources
[Numbered list of all URLs cited in the report]
```

**Core rules:**
- Ev