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/event-prospecting

@592061a official
by browserbasebrowserbase/skills3.7k stars
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Event prospecting skill. Takes a conference / event speakers URL, extracts the people, filters their companies against the user's ICP, then deep-researches only the speakers at ICP-fit companies. Outputs a person-first HTML report where each card answers "why should the AE talk to this person?" with all public links and a one-click DM opener. Use when the user wants to: (1) find leads at a specific conference, (2) prep for an event, (3) research event speakers, (4) build a target list from a sponsor/exhibitor page, (5) scrape conference speakers and rank by ICP fit. Triggers: "find leads at {event}", "research speakers at", "prospect this conference", "stripe sessions leads", "ai engineer summit prospects", "event prospecting", "scrape conference speakers", "who should I meet at".

Ask your Agent

Use this Skill: https://skilld.dev/gh/browserbase/skills/event-prospecting

This session only. Nothing lands on disk.

referencesexample-research.md

≈2.2k tokens on demand. Your agent reads this file only when SKILL.md points to it.

Example Research Files

Event-prospecting writes TWO kinds of markdown files:

  1. Company files — one per company in seed_companies.txt, written to {OUTPUT_DIR}/companies/{slug}.md. Comes in two flavors: triage stubs (Step 5) and deep-research files (Step 7).
  2. Person files — one per speaker at an ICP-fit company, written to {OUTPUT_DIR}/people/{slug}.md. Created in Step 8.

The YAML frontmatter contains structured fields for report compilation. The body contains human-readable research.

{OUTPUT_DIR} is the per-run Desktop directory set up by the main agent in Step 0 (e.g., /Users/jay/Desktop/{event_slug}_prospects_2026-04-25-2030/).

Company File — Triage Stub (Step 5 output)

Every company in seed_companies.txt gets one of these. It captures a 1-call, ICP-only assessment.

---
company_name: OpenAI
website: https://openai.com
product_description: AI lab building safe AGI; ChatGPT, GPT API, ChatGPT Agent
icp_fit_score: 9
icp_fit_reasoning: AI agents at scale need cloud browser infrastructure; ChatGPT Agent shipped Mar 2026
triage_only: true
event_context: Stripe Sessions 2026 — featured speaker on AI track
---

## Triage Notes
Homepage: "ChatGPT, GPT API, and ChatGPT Agent — AI tools and APIs for everyone."
Score 9 because ChatGPT Agent ships browser-using AI agents at consumer scale — the canonical fit for browser infrastructure.

Required fields: company_name, website, icp_fit_score, icp_fit_reasoning, triage_only: true.

Company File — Deep Research (Step 7 output)

When a company's icp_fit_score >= --icp-threshold, Step 7's deep research overwrites the triage stub with this richer version. triage_only flips to false.

---
company_name: OpenAI
website: https://openai.com
product_description: Foundational AI lab; products span ChatGPT (consumer chat), GPT API (developer access), and ChatGPT Agent (browser-using autonomous agent)
industry: AI / Foundation Models
target_audience: Consumers, developers, enterprise — multi-segment
key_features: ChatGPT Agent | GPT-5 API | Sora video | enterprise data residency
icp_fit_score: 9
icp_fit_reasoning: ChatGPT Agent (Mar 2026) is a browser-using agent at consumer scale — directly addresses the "agents need a browser" wedge. Plus enterprise customers ship internal agents on top of GPT API.
employee_estimate: 3000+
funding_info: $11.3B raised; reported $300B valuation 2026
headquarters: San Francisco, CA
triage_only: false
event_context: Stripe Sessions 2026 — Greg Brockman featured speaker, Agents track
event_relevance: Three OpenAI speakers across the Agents and Infra tracks; ChatGPT Agent demo expected at the event
---

## Product
Foundational AI lab. Three product surfaces: ChatGPT (consumer/team chat), GPT API (developer platform), ChatGPT Agent (autonomous browsing agent that completes multi-step tasks). Recently shipped Sora 2 for video.

## Research Findings
- **[high]** ChatGPT Agent launched Mar 2026 — autonomous web-browsing agent that books, shops, and researches on user's behalf (source: openai.com/index/chatgpt-agent)
- **[high]** Stripe Sessions 2026 keynote includes Greg Brockman on the Agents track (source: stripesessions.com/speakers)
- **[medium]** Hiring across "Agent Reliability" team — 12 open roles for browser-automation engineers (source: openai.com/careers, search 2026-04)
- **[medium]** Reported partnership exploration with infrastructure providers for agent runtime (source: The Information, 2026-03)

## Event Relevance
Three speakers at Stripe Sessions across Agents and Infra tracks. ChatGPT Agent is the canonical use-case for browser-infrastructure-as-a-product. Pitch angle: durability + scale guarantees the in-house Browserbase-equivalent can't easily match.

Additional fields vs the stub: industry, target_audience, key_features (pipe-separated), employee_estimate, funding_info, headquarters, event_relevance.

Body sections: ## Product, ## Research Findings, ## Event Relevance.

Person File (Step 8 output)

Only created for speakers at ICP-fit companies (those whose company file has triage_only: false after Step 7).

---
name: Greg Brockman
slug: greg-brockman
company: OpenAI
company_slug: openai
title: President & Co-founder
image: https://cdn.example.com/speakers/greg-brockman.jpg
links:
  linkedin: https://www.linkedin.com/in/thegdb/
  x: https://x.com/gdb
  github: https://github.com/gdb
  blog: null
  podcast: https://lexfridman.com/greg-brockman/
hook: Recent Lex Fridman conversation on agent reliability — direct fit for the browser-infrastructure durability story
dm_opener: |
  Hey Greg — caught your Lex conversation on agent reliability and the
  "agents are bottlenecked on the browser" framing landed hard. We run
  the cloud-browser layer that ChatGPT Agent's competitors are shipping
  on. Worth a 15-min walkthrough before Sessions?
role_reason: Co-founder, sets infrastructure direction across product surfaces
event_name: Stripe Sessions 2026
event_context: Panelist, Agents track ("From demo to dependable: making agents reliable")
icp_fit_score: 9
icp_fit_reasoning: AI agents at scale need cloud browser infrastructure; ChatGPT Agent shipped Mar 2026
enriched_at: 2026-04-25T20:30:00Z
---

## Why reach out
- **Why the company**: ChatGPT Agent is the canonical browser-infra customer — see `companies/openai.md`
- **Why the person**: Co-founder; sets infra direction; specifically called out agent reliability on Lex (Mar 2026)
- **Hook**: Lex Fridman conversation on agent reliability (45 min, dropped 2026-03-12)

## Public links
- LinkedIn: https://www.linkedin.com/in/thegdb/
- X: https://x.com/gdb
- GitHub: https://github.com/gdb (OpenAI / personal)
- Podcast: https://lexfridman.com/greg-brockman/

## Recent activity
- **[high]** Lex Fridman podcast episode on agent reliability, Mar 2026 (source: lexfridman.com/greg-brockman)
- **[medium]** GitHub activity: contributed to openai/chatgpt-agent-evals (source: github.com/gdb)
- **[medium]** X thread on "the bottleneck for agents is the browser, not the model" — Apr 2026 (source: x.com/gdb)

Required fields: name, slug, company, links (object), hook, dm_opener, role_reason, event_name, event_context, icp_fit_score.

Body sections: ## Why reach out (3 bullets that mirror the card), ## Public links, ## Recent activity (findings list with confidence levels).

Field Rules

Company files

  • key_features: pipe-separated (|) list, NOT a JSON array
  • icp_fit_score: integer 1-10
  • icp_fit_reasoning: one line, references specific findings
  • triage_only: boolean (true for stubs, false after deep research)
  • event_context: how this company shows up at the event (sponsor tier, speaker count, track topics)
  • Filename: {OUTPUT_DIR}/companies/{slug}.md where slug is lowercase, hyphenated

Person files

  • image: speaker headshot URL extracted from the event site (preserved verbatim from the people.jsonl input record). May be null on platforms that don't expose it.
  • links: YAML object with keys linkedin, x, github, blog, podcast. Use null when not found, not empty string.
  • hook: one sentence, sourced from a specific finding (event-context, recent activity, or company-context). Never inferred from memory.
  • dm_opener: 2-3 sentences, multi-line YAML string with | pipe. References the hook, names a wedge tie-in, ends with a soft CTA.
  • icp_fit_score is INHERITED from the corresponding companies/{company_slug}.md — keeps cards rankable in the index.
  • Filename: {OUTPUT_DIR}/people/{slug}.md where slug is the lowercased + hyphenated person name (e.g. greg-brockman.md).

Both

  • One file per entity. If a subagent encounters a duplicate, OVERWRITE with richer data (e.g. Step 7 overwrites Step 5's triage stub for the same company).

Writing via Bash Heredoc

Subagents write these files using bash heredoc to avoid security prompts. Use the full literal {OUTPUT_DIR} path — no ~ or $HOME:

cat << 'PERSON_MD' > /Users/jay/Desktop/stripesessions_prospects_2026-04-25-2030/people/greg-brockman.md
---
name: Greg Brockman
slug: greg-brockman
...
---

## Why reach out
...
PERSON_MD

Use 'PERSON_MD' (quoted) as the delimiter to prevent shell variable expansion. Use 'COMPANY_MD' for company files.

IMPORTANT: Write ALL files in a SINGLE Bash call using chained heredocs to minimize permission prompts. One subagent batch (~5 people) = one Bash invocation = one permission prompt.

cat << 'PERSON_MD' > {OUTPUT_DIR}/people/greg-brockman.md
---
...
---
PERSON_MD
cat << 'PERSON_MD' > {OUTPUT_DIR}/people/sam-altman.md
---
...
---
PERSON_MD

Chained heredocs in one bash call. The subagent reports back ONLY a count, never raw content.

Source: SKILL.md on GitHub

Third-party checks

1 warning16d3 checks · Risk SAFE
  • Gen Agent Trust Hub16d

    The event-prospecting skill automates lead discovery from conference websites by scraping speaker lists, performing ICP-based company triage, and enriching contact data. It generates a comprehensive local HTML report and CSV export.

  • Socket16d

    No alerts

  • Snyk16d

    Risk: MEDIUM · 2 issues

Provenance

Signed by skilld at 592061a. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub last month.

Activeupdated 5 months ago

Capability

metadata
{
  "author": "browserbase",
  "version": "0.1.0"
}
All 1 allowed tools
Bash Agent AskUserQuestion
Other metadata
compatibility
Requires browse CLI (`npm install -g browse`) and BROWSERBASE_API_KEY env var. The same `browse` binary covers both API commands and JS-rendered page fallback.

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