List Expander

What it does

When your agent uses it

• A vertical list feels too small (medical groups
• Medicare brokerages)
• Known good-fit companies dont show up in keyword searches
• Someone says expand this list

Example prompts

• “too small”
• “t show up in keyword searches, or when someone says”
• “the TAM should be bigger”
• “/list-expander”

Requirements

• Node.js
• A credential in PROSPEO_API_KEY
• A credential in OPENAI_API_KEY

Workflow steps

6 steps, taken from the step headings in SKILL.md.

1. 1inputs
2. 2fingerprint the seeds
3. 3generate lookalikes
4. 4mine + score filters
5. 5wide pull + scale qualification
6. 6TAM ceiling + report

What it can do on your machine

Read from SKILL.md and the folder at commit 25c5d85. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships 9 files in scripts/ (TypeScript), which the agent can run.

  Shell commands in SKILL.md call:

  • npx

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Links to these hosts (documentation or services it may open):

  • platform.openai.com
  • prospeo.io
  • exa.ai
  • parallel.ai

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names these keys or tokens, usually read from environment variables:

  • OPENAI_API_KEY
  • PROSPEO_API_KEY
  • EXA_API_KEY
  • PARALLEL_AI_API_KEY

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

List Expander loads about 2.7k tokens when it runs. Until then it costs about 183 tokens; SKILL.md has 878 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~183

When it runs · the whole SKILL.md, loaded when a task matches

~2.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

• NoteMentions a .env fileSKILL.md:20

  `--help`. Keys load from the repo-root `.env` (see `.env.example`),

• NoteMentions a .env fileSKILL.md:21

  falling back to `~/.env`. Artifacts land in `~/output/list-expander/{run}/`.

• NoteMentions a .env fileSKILL.md:120

  Put these in the repo-root `.env` (copy `.env.example`), or `~/.env`.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from growthenginenowoslawski/coldoutboundskills at commit 25c5d85, republished under its MIT licence (© growthenginenowoslawski). 878 words, ~2,677 tokens.

name

list-expander

description

Expand a hard-to-build niche list from ~10 known-good seed companies into a full qualified TAM. Seed fingerprinting (how do good-fit companies ACTUALLY show up in the company database's filters) → lookalike generation (Prospeo company_lookalike, Exa findSimilar, Parallel.ai entity search) → filter mining with a precision/volume scorecard → wide pull with auto-sharding → cheap-AI qualification → live-website verification → client transparency report. Use when a vertical list feels "too small" (medical groups, hedge funds, Medicare brokerages), when known good-fit companies don't show up in keyword searches, or when someone says "expand this list", "the TAM should be bigger", "find more companies like these".

Phase 1  fingerprint.ts    seeds → how each shows up in Prospeo + its live homepage
Phase 2  lookalikes.ts     seeds → candidates via Prospeo lookalike + Exa + Parallel
                           (qualify candidates → lookalikes-confirmed.csv)
Phase 3  mine-filters.ts   confirmed fits → candidate filters → scorecard (volume × precision)
Phase 4  pull.ts           winning filters → wide pull, auto-shard, dedup, exclusions
         score-batch.ts    scale AI qualification (gpt-5-nano by default)
         verify-website.ts second pass on QUALIFIED rows: live homepage fetch →
                           dead / suspended-parked / live; live sites re-judged on
                           their CURRENT content (catches stale-DB ghosts). Always run —
                           DB descriptions happily qualify dead companies otherwise.
Phase 5  contact-count.ts  verified-email TAM ceiling (free Prospeo count trick)
         report.ts         single-file HTML transparency report for the client

npx tsx scripts/fingerprint.ts --domains="a.com,b.com,..." --run=<slug>

npx tsx scripts/lookalikes.ts --domains="<seeds>" --run=<slug> \
  --objective="<NL description of the COMPANY TYPE (not your product!)>" \
  --country="United States #US" --pages=3

npx tsx scripts/mine-filters.ts --csv=<confirmed.csv> --run=<slug> --propose --country="United States #US"
# Claude reviews/edits {run}/candidates.json: prune generic n-grams, add synonym keywords
# (the "every medical group contains 'group'" trap — kill terms that are frequent but not discriminative)
npx tsx scripts/mine-filters.ts --run=<slug> --scorecard
# score the 25-company samples:
for f in ~/output/list-expander/<slug>/samples/*.csv; do
  npx tsx scripts/score-batch.ts --csv=$f --prompt-file=<icp-prompt.txt> --out=${f%.csv}-scored.csv; done
mkdir -p ~/output/list-expander/<slug>/samples-scored && mv ~/output/list-expander/<slug>/samples/*-scored.csv $_
npx tsx scripts/mine-filters.ts --run=<slug> --scorecard --precision-from=~/output/list-expander/<slug>/samples-scored

# Write {run}/winners.json (filter_sets + base_filters — format documented in pull.ts header)
npx tsx scripts/pull.ts --run=<slug> --test          # 2 pages/set sanity check FIRST
npx tsx scripts/pull.ts --run=<slug> --exclude=<existing.csv>
npx tsx scripts/score-batch.ts --csv=<run>/pull-all.csv --prompt-file=<icp-prompt.txt> --scrape --concurrency=8
npx tsx scripts/verify-website.ts --run=<slug> --prompt-file=<icp-prompt.txt> --concurrency=40

npx tsx scripts/contact-count.ts --csv=<qualified.csv> --run=<slug> \
  --titles="COO,VP Operations,..." --seniorities="C-Suite,Vice President,Head,Director"
npx tsx scripts/report.ts --run=<slug> --title="<Vertical> — TAM Expansion"
open ~/output/list-expander/<slug>/report.html

© growthenginenowoslawski, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 9 other files (scripts) in skills/list-expander of growthenginenowoslawski/coldoutboundskills.

• SKILL.md
• scripts/contact-count.ts
• scripts/fingerprint.ts
• scripts/lib.ts
• scripts/lookalikes.ts
• scripts/mine-filters.ts
• scripts/pull.ts
• scripts/report.ts
• scripts/score-batch.ts
• scripts/verify-website.ts

Open the folder on GitHubat commit 25c5d85