event-prospecting

What this skill does

# Event Prospecting

Take a conference URL → get a ranked list of people the AE should talk to, with a "why reach out" rationale per person.

**Required**: `BROWSERBASE_API_KEY` env var and the `browse` CLI installed (`npm install -g browse`). Use `browse cloud ...` for API calls and `browse open` / `browse get markdown` for JS-heavy speaker pages.

**Path rules**: Always use the full literal path in all Bash commands — NOT `~` or `$HOME` (both trigger "shell expansion syntax" approval prompts). Resolve the home directory once and use it everywhere. When constructing subagent prompts, replace `{SKILL_DIR}` with the full literal path (typically `/Users/jay/skills/skills/event-prospecting`).

**Output directory**: All event prospecting output goes to `~/Desktop/{event_slug}_prospects_{YYYY-MM-DD-HHMM}/`. Final deliverable is `index.html` (people grouped by company, ranked by company ICP), with `companies.html` and `people.html` (filterable) as alternate views, plus `results.csv` for cold-outbound import.

**CRITICAL — Tool restrictions (applies to main agent AND all subagents)**:
- All web searches: use `browse cloud search`. NEVER use WebSearch.
- All page content extraction: use `node {SKILL_DIR}/scripts/extract_page.mjs "<url>"`. This script fetches via `browse cloud fetch --output`, parses title + meta tags + visible body text, and automatically falls back to `browse get markdown` when fetch fails or returns thin JS-rendered content. NEVER hand-roll a `browse cloud fetch | sed` pipeline. NEVER use WebFetch.
- All research output: subagents write **one markdown file per company OR per person** to `{OUTPUT_DIR}/companies/{slug}.md` or `{OUTPUT_DIR}/people/{slug}.md` using bash heredoc. NEVER use the Write tool or `python3 -c`. See `references/example-research.md` for both file formats.
- Report compilation: use `node {SKILL_DIR}/scripts/compile_report.mjs {OUTPUT_DIR} --open`.
- **Subagents must use ONLY the Bash tool. No other tools allowed.**
- **HARD TOOL-CALL CAPS**: ICP triage = 1 call/company; deep research = 5 calls/company; person enrichment = 4 calls/person. See `references/workflow.md` for enforcement detail.

**CRITICAL — Anti-hallucination rules (applies to main agent AND all subagents)**:
- NEVER infer `product_description`, `industry`, or a person's `role_reason` from a site's fonts, framework, design system, or typography. These are cosmetic and say nothing about what the company sells or what the person does.
- NEVER let the user's own ICP leak into a target's description. If you don't know what the target does, write `Unknown` — do not pattern-match them onto the ICP.
- `product_description` MUST quote or paraphrase a specific phrase from `extract_page.mjs` output. If none of TITLE/META/OG/HEADINGS/BODY yield a recognizable product statement, write `Unknown — homepage content not accessible` and cap `icp_fit_score` at 3.
- A person's `hook` MUST quote or paraphrase a specific finding from a `browse cloud search` result (podcast title, blog headline, GitHub repo, talk abstract). If no public signal exists in the last 6 months, fall back to event-context (their talk title at this event).

**CRITICAL — Minimize permission prompts**:
- Subagents MUST batch ALL file writes into a SINGLE Bash call using chained heredocs. One Bash call = one permission prompt.
- Batch ALL searches and ALL fetches into single Bash calls using `&&` chaining.

## Pipeline Overview

Follow these 10 steps in order. Do not skip steps or reorder.

0. **Setup** — output dir + clean slate
1. **Load profile** — read `profiles/{user_slug}.json`
2. **Recon** — detect event platform
3. **Extract people** — `people.jsonl`
4. **Group by company** — `seed_companies.txt`
5. **ICP triage** — fast company-level scoring (1 call/company)
6. **Filter** — companies with `icp_fit_score >= --icp-threshold`
7. **Deep research** — full Plan→Research→Synthesize on ICP fits
8. **Enrich speakers** — ask user: ICP-fit only (default) or all speakers
9. **Compile report** — HTML + CSV, open in browser

The user invokes the skill with a URL like `/event-prospecting <URL>`. Parse `EVENT_URL` from that invocation message. Defaults: `DEPTH=deep`, `ICP_THRESHOLD=6`. The `USER_SLUG` (ICP profile) is auto-resolved in Step 1 from whatever profile files exist locally — there is no built-in default profile. Do NOT ask the user to confirm the URL — they already gave you it.

---

## Step 0: Setup Output Directory

Derive the output directory from the URL the user gave you. Do NOT hardcode any event name.

```bash
# EVENT_URL came from the invocation message (whatever the user typed after `/event-prospecting`)
EVENT_SLUG=$(node -e 'const h = new URL(process.argv[1]).hostname.replace(/^www\./,""); console.log(h.split(".")[0])' "$EVENT_URL")
TIMESTAMP=$(date +%Y-%m-%d-%H%M)
OUTPUT_DIR=/Users/jay/Desktop/${EVENT_SLUG}_prospects_${TIMESTAMP}
mkdir -p "$OUTPUT_DIR/companies" "$OUTPUT_DIR/people"
```

Use the full literal home path — never `~` or `$HOME`. Pass `{OUTPUT_DIR}` as the full literal path to all subagent prompts.

## Step 1: Load User Profile

The profile defines the ICP that ICP triage and deep research score against. Load from `{SKILL_DIR}/profiles/{user_slug}.json` (interchangeable across all GTM skills — same shape as company-research). `example.json` is a template, not a real profile — never use it.

**DO NOT look outside `{SKILL_DIR}/profiles/`** for profiles — never reach into other skills' directories. If a profile is needed elsewhere, the user copies it explicitly.

**Resolution order**:
1. If the user invoked with `--user-company <slug>`, use that slug.
2. Else, list `profiles/*.json` excluding `example.json`. If exactly one profile exists, use it (and tell the user which one). If multiple exist, ask the user (plain chat) which one.
3. If zero profiles exist, **fail loudly** and instruct the user to create one (copy `profiles/example.json` to `profiles/<your_slug>.json` and fill it in, or run the company-research skill which builds one automatically).

```bash
PROFILES=$(ls {SKILL_DIR}/profiles/*.json 2>/dev/null | xargs -n1 basename | sed 's/\.json$//' | grep -v '^example$')
COUNT=$(echo "$PROFILES" | grep -c .)

if [ -z "$USER_SLUG" ]; then
  if [ "$COUNT" -eq 0 ]; then
    echo "No profiles found in {SKILL_DIR}/profiles/. Copy profiles/example.json to profiles/<your_slug>.json and fill it in, or run the company-research skill to build one."
    exit 1
  elif [ "$COUNT" -eq 1 ]; then
    USER_SLUG=$PROFILES
    echo "Using the only profile available: ${USER_SLUG}"
  else
    echo "Multiple profiles found:"
    echo "$PROFILES" | sed 's/^/  - /'
    echo "Re-invoke with --user-company <slug> to pick one."
    exit 1
  fi
fi

test -f {SKILL_DIR}/profiles/${USER_SLUG}.json || {
  echo "Profile not found: profiles/${USER_SLUG}.json"
  exit 1
}
cat {SKILL_DIR}/profiles/${USER_SLUG}.json
```

The profile yields: `company`, `product`, `icp_description`, `existing_customers`. These get embedded verbatim in every subagent prompt downstream.

## Step 2: Recon

Detect the event platform and extraction strategy. One command:

```bash
node {SKILL_DIR}/scripts/recon.mjs {EVENT_URL} {OUTPUT_DIR}
```

Writes `{OUTPUT_DIR}/recon.json` with `platform`, `strategy`, and (for Next.js) `nextDataPaths`. See `references/event-platforms.md` for the platform catalog and detection priority.

Expected outcomes:
- Stripe Sessions class (Next.js): `platform: "next-data"`, 1-3 paths
- Sessionize: `platform: "sessionize"`
- Lu.ma / Eventbrite: `platform: "luma" | "eventbrite"`
- Anything else: `platform: "custom"`, `strategy: "markdown"` (best-effort fallback)

## Step 3: Extract People

```bash
node {SKILL_DIR}/scripts/extract_event.mjs {OUTPUT_DIR} --user-company {USER_SLUG}
```

Reads `recon.json`, dispatches to the platform-specific extractor, writes `people.jsonl` (one speaker per line) and `seed_companies.txt` (deduped companies).

The `--user-company` flag also drops the host-org's own employees (a Stripe-