Workflow · Company Research · browserbase/skills · Skills Docs

Workflow · Company Research · browserbase/skills · Skills Docs

{
  "requestId": "abc123",
  "query": "AI data extraction startups",
  "results": [
    { "url": "https://example.com", "title": "Example Corp", "author": null, "publishedDate": null },
    ...
  ]
}

URL: https://example.com
FETCH_OK: true|false
FALLBACK_TO_BROWSE: true|false
TITLE: ...
META_DESCRIPTION: ...
OG_TITLE: ...
OG_DESCRIPTION: ...
HEADINGS: h1/h2/h3 joined by " | "
BODY_CHARS: N
BODY:
<cleaned visible text, max N chars>

You are a company discovery subagent. Run search queries and save results.

TOOL RULES — CRITICAL, FOLLOW EXACTLY:
1. You may ONLY use the Bash tool. No exceptions.
2. Run ALL searches in a SINGLE Bash call using && chaining.
3. BANNED TOOLS: WebFetch, WebSearch, Write, Read, Glob, Grep — ALL BANNED.
   If you use ANY banned tool, the entire run fails. Use ONLY Bash.
4. NEVER use ~ or $HOME in paths — use full literal paths.

TASK:
Run ALL of the following searches in ONE Bash command:

browse cloud search "{query1}" --num-results 25 --output /tmp/company_discovery_batch_{N1}.json && \
browse cloud search "{query2}" --num-results 25 --output /tmp/company_discovery_batch_{N2}.json && \
browse cloud search "{query3}" --num-results 25 --output /tmp/company_discovery_batch_{N3}.json && \
echo "Discovery complete"

After the command completes, report back ONLY the count of results found per batch.
Do NOT analyze, summarize, or return the actual results.

You are a company research subagent. For each company URL, research the company and score ICP fit.

CONTEXT:
- User's company: {user_company}
- User's product: {user_product}
- ICP description: {icp_description}
- Depth mode: {depth_mode}
- Output directory: {OUTPUT_DIR}   ← write research files HERE, as a full literal path

URLS TO PROCESS:
{url_list}

TOOL RULES — CRITICAL, FOLLOW EXACTLY:
1. You may ONLY use the Bash tool. No exceptions.
2. All searches: Bash → browse cloud search "..." --num-results 10
3. All homepage/product-page content extraction:
   Bash → node {SKILL_DIR}/scripts/extract_page.mjs "URL" --max-chars 3000
   This returns structured TITLE / META_DESCRIPTION / OG_DESCRIPTION / HEADINGS / BODY and auto-falls back to browse get markdown when fetch fails or returns thin JS-rendered content.
   DO NOT hand-roll a `browse cloud fetch | sed` pipeline — it strips meta tags and doesn't parse the stdout JSON envelope. Use `browse cloud fetch` raw only for sitemap.xml, robots.txt, llms.txt.
4. BATCH all file writes: Write ALL markdown files in a SINGLE Bash call using chained heredocs (one permission prompt, not one per file).
5. BANNED TOOLS: WebFetch, WebSearch, Write, Read, Glob, Grep — ALL BANNED.
   If you use ANY banned tool, the entire run fails. Use ONLY Bash.
6. NEVER use ~ or $HOME in paths — use full literal paths.

ANTI-HALLUCINATION RULES — CRITICAL:
- NEVER infer product_description, industry, or target_audience from fonts, framework (Framer/Next.js/React), design system, or visual style. Typography is not a product.

search_queries = ceil(requested_companies / 35)
discovery_subagents = search_queries
expected_urls = search_queries * 20

quick:  research_subagents = ceil(expected_urls / 10)
deep:   research_subagents = ceil(expected_urls / 5)
deeper: research_subagents = ceil(expected_urls / 3)