# Autumn Prospect Research

> Given a company or person, run structured prospect research and synthesize a brief covering what they do, recent signals, likely pain points, and a tailored outbound hook.

- Skill: `riteshkew/autumn-prospect-research` (Agent Skill, multi-file: 9 files)
- Install (CLI): `npx skillmds@latest add riteshkew/autumn-prospect-research`
- Raw SKILL.md: https://api.skillmd.com/api/skills/riteshkew/autumn-prospect-research/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Research & Search
- Author: riteshkew (https://skillmd.com/u/riteshkew)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/riteshkew/autumn-prospect-research

---


# Workflow

When this skill triggers, follow these steps in order.

## Step 1 — Identify the research target

Ask the user for the company or person name and (optionally) their website URL.

- If a URL is provided, use it with the `--live` flag for a live fetch.
- If only a name is provided, use web search to locate the canonical URL before fetching.
- If neither is available, offer to run the built-in example against the committed cached fixture for Y Combinator.

## Step 2 — Fetch and extract

Run the research engine against the target:

**Offline / cached mode** (default — no network required):
```bash
node scripts/research.mjs
```
Reads `resources/ycombinator-cached.html` and extracts facts from the committed fixture.

**Live mode** (requires network access):
```bash
node scripts/research.mjs --live <url>
```
Fetches the URL using Node's built-in `fetch`, then runs the same extraction pipeline.

The engine:
1. Strips HTML tags and normalizes whitespace to plain text.
2. Extracts the page title, meta description, and notable bullet lines.
3. Identifies the company name, what they do, and notable statistics or signals.

## Step 3 — Synthesize the brief

The engine writes a structured Markdown brief with five sections:

| Section | Content |
|---------|---------|
| **Company** | Name extracted from the page title |
| **What They Do** | Meta description or first meaningful paragraph |
| **Signals / Notables** | Bullet lines from the page (stats, dates, funding, news) |
| **Likely Pain Points** | Inferred from keyword analysis of the extracted text |
| **Suggested Hook** | A tailored opening line for an outbound message |

## Step 4 — Deliver and iterate

Present the brief to the user. Offer to:

- Refine the hook for a specific product or angle.
- Add competitive context if the user provides a competitor name.
- Re-run with a different URL or a fresh live fetch.

## Example

The committed example researches **Y Combinator** using the cached fixture:

```bash
cd skills/autumn-prospect-research
bash examples/run.sh
```

Output is written to `examples/output.md`. See `examples/input.md` for the research request.

The committed proof is fully deterministic and offline. In a live session, Claude uses web search and the `--live` flag to research any target in real time.