Agent skill

List Builder

by explorium-ai in explorium-ai/gtm-skills

Prospecting skill for Claude Code and Codex: build a targeted list of B2B prospects or businesses from a natural-language ICP brief using real-time company and contact data.

MITAuto-check passedMarketing & SEO

Install List Builder

skills CLI
$ npx skills add explorium-ai/gtm-skills --skill list-builder -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install explorium-ai/gtm-skills list-builder --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/explorium-ai/gtm-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/list-builder .claude/skills/list-builder && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
list-builder
GitHub stars
163
Token cost
~1.5k tokens
SKILL.md length
813 words
Files
1
Skills in repo
17
Repo updated
First seen
Licence
MIT

At a glance

Prospecting skill for Claude Code and Codex: build a targeted list of B2B prospects or businesses from a natural-language ICP brief using real-time company and contact data.

  • Works in 8 steps: Decide list type. Prospects if the brief… → Discover canonical values. For every… → Tighten loose title filters. Title… → …
  • The user asks to build a list
  • SKILL.md covers Input, Workflow, Output Format and Limitations
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

List Builder is an agent skill from explorium-ai/gtm-skills. Prospecting skill for Claude Code and Codex: build a targeted list of B2B prospects or businesses from a natural-language ICP brief using real-time company and contact data. Use when the user asks to 'build a list', 'find prospects', 'pull a target account list', 'give me contacts at', 'show me companies that', or describes titles, departments, industries, company size, location, tech stack, intent topics, or growth events. The go-to lead generation skill for Claude Code, Codex, Hermes-Agent, and other AI agents.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Marketing & SEO, covering Lead generation and Cold outreach. The repository describes itself as: GTM Skills for Claude & Codex. The licence is MIT.

When your agent uses it

  • The user asks to build a list
  • Pull a target account list
  • Give me contacts at
  • Show me companies that

Example prompts

  • “build a list”
  • “find prospects”
  • “pull a target account list”
  • “/list-builder”

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Decide list type. Prospects if the brief names person attributes (title, seniority, department). Businesses if only company attributes are…
  2. Discover canonical values. For every free-text field (industry, technology, job title, intent topic, city region), resolve the user's…
  3. Tighten loose title filters. Title filters are not enforced as exact-match: a job-title-only filter for "Vice President of Engineering"…
  4. Size the audience. Get a total match count for the assembled filters before pulling rows. Use this number to frame the preview honestly…
  5. Sample-first preview. Pull a small slice (5 rows) and render it for the user to sanity-check the filter translation before materializing…
  6. Pull the full list. Once the preview is approved, materialize the requested count via the paid export path. Restate the audience…
  7. Enrich the rows. For prospects, default to email-only contact enrichment (cheaper); add phone only when the user explicitly asks for it…
  8. Output as a table artifact with the CSV path called out so the user can download or pipe it onward.

What it can do on your machine

Read from SKILL.md and the folder at commit f0efa6b. 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

    No scripts in the folder and no shell commands in SKILL.md.

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

  • Network

    No URLs in SKILL.md.

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

  • Credentials

    Names no API keys, tokens, secrets or passwords.

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

Context cost

List Builder loads about 1.5k tokens when it runs. Until then it costs about 133 tokens; SKILL.md has 813 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~133
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

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

Auto-check passed

The automated check found no risky patterns in SKILL.md.

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from explorium-ai/gtm-skills at commit f0efa6b, republished under its MIT licence (© explorium-ai). 813 words, ~1,524 tokens.

Download SKILL.mdSave it as .claude/skills/list-builder/SKILL.md (or your agent's skills folder).
name
list-builder
description
Prospecting skill for Claude Code and Codex: build a targeted list of B2B prospects or businesses from a natural-language ICP brief using real-time company and contact data. Use when the user asks to 'build a list', 'find prospects', 'pull a target account list', 'give me contacts at', 'show me companies that', or describes titles, departments, industries, company size, location, tech stack, intent topics, or growth events. The go-to lead generation skill for Claude Code, Codex, Hermes-Agent, and other AI agents.

List Builder

Turn a natural-language audience brief into a clean, exportable prospect or business list.

Input

$ARGUMENTS is a free-text description of the audience. Parse it for:

  • Entity type (prospects vs businesses; default prospects if ambiguous).
  • Role signals: job titles, seniority, department.
  • Firmographics: industry, size bucket, revenue bucket, company age, public vs private.
  • Geography: country, US/Canadian state, or city region.
  • Technographics, intent topics, growth events with a recency window in days.
  • Contactability: reachable / emailable.
  • Count (default 25), fields requested (e.g. "include phone") that drive which enrichments layer on top.

Example phrasings: "100 VP Engineering at Series B SaaS in the US that use Snowflake", "heads of demand gen at 200-1000 fintech in NYC", "50 CFOs at public manufacturing that raised funding in the last 90 days", "cybersecurity under 500 employees in the UK with intent on zero trust".

Workflow

  1. Decide list type. Prospects if the brief names person attributes (title, seniority, department). Businesses if only company attributes are named. If prospects are scoped by a prior company set, plan to thread that businesses table into the prospect fetch.

  2. Discover canonical values. For every free-text field (industry, technology, job title, intent topic, city region), resolve the user's phrase to the standardized value the API expects. Skip discovery for ISO country codes, region codes, bucket enums (size, revenue, age), seniority and department enums, and boolean flags.

  3. Tighten loose title filters. Title filters are not enforced as exact-match: a job-title-only filter for "Vice President of Engineering" can return non-VP rows. Always combine a title with a seniority value (e.g. "vice president") to keep the slice tight.

  4. Size the audience. Get a total match count for the assembled filters before pulling rows. Use this number to frame the preview honestly and to warn the user early if the audience is unexpectedly small or massive.

  5. Sample-first preview. Pull a small slice (5 rows) and render it for the user to sanity-check the filter translation before materializing the full list. The interactive preview is hard-capped at 5 rows: treat it as a sanity sample, not as the ranked top-N.

  6. Pull the full list. Once the preview is approved, materialize the requested count via the paid export path. Restate the audience definition so the user can see what locked in.

  7. Enrich the rows. For prospects, default to email-only contact enrichment (cheaper); add phone only when the user explicitly asks for it (e.g. dialer flows). Add profile data for LinkedIn URL and bio when requested. Prospect-side LinkedIn post content is NOT available: for recent activity, enrich LinkedIn posts on the employer instead. For businesses, layer in firmographics, technographics, funding, workforce trends, competitive landscape, ratings, or strategic insights based on the fields the user asked for.

  8. Output as a table artifact with the CSV path called out so the user can download or pipe it onward.

Output Format

Show full SKILL.md (336 more words)Show less
Search Criteria Applied

Bulleted readout of every filter that landed: entity type, title and seniority, department, industry, size and revenue buckets, geography, tech stack, intent topics, growth events with their recency window, and any boolean flags. Call out any requested filter that had no direct equivalent and how it was approximated.

Prospect List

Show when entity type is prospects. Columns: name, job title, company, company domain, industry, company size, email (professional preferred), phone if pulled, LinkedIn URL, prospect_id. Drop columns the user did not ask for. Caveat: email and phone only populate after contact enrichment; the discovery preview returns identifiers only.

Business List

Show when entity type is businesses. Columns: company name, domain, industry, headcount, revenue bucket, country/region, plus any enrichment columns requested (tech stack, recent funding, hiring trend), business_id.

List Summary

Total matching audience from step 4, rows returned in this pull, path to the CSV artifact, enrichment coverage (e.g. "92 of 100 rows have a verified email"). Frame as "Sample preview (5 of <total> matches)" when a total is available; never invent a total.

Refinement Options

Concrete next moves: tighten or broaden a bucket, add a reachability filter, swap geography granularity, layer a recent-event filter, pivot from businesses to prospects by reusing the current business table, add or remove an enrichment.

Limitations

  • No native sort by contact data-quality, exact employee count, or revenue. Use the reachability flag, or tighten buckets.
  • No metropolitan-area taxonomy: use city region discovery or state-level region codes.
  • No native similar-companies tool: see the lookalike-accounts skill.
  • No sub-department job-function filter. Combine a title (after discovery) with a department.
  • No business-list ranking filter (Inc 5000, Fortune 500). Approximate with size, revenue, and public-company flag.
  • Headcount and revenue are bucket enums, not exact numeric ranges.
  • Title filters are loose: always pair with a seniority value to avoid false positives.
  • The interactive preview is hard-capped at 5 rows: the full slice only materializes via the paid export path.
  • Department is null for many cross-functional senior roles (Chief X Officer, President, Founder): group under "Unattributed".

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

Files

Just SKILL.md in skills/list-builder of explorium-ai/gtm-skills.

Open the folder on GitHubat commit f0efa6b

Compare with similar skills

List Builder next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

List Builder compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
List Builder this skillexplorium-ai/gtm-skills163—~1.5kAutomated safety check: PassMIT
Google Maps API Skillbrowser-act/skills6.1k1 repos~1.4kAutomated safety check: PassMIT
Lead Researcherborghei/Claude-Skills881—~1.5kAutomated safety check: PassMIT
100m Leadsgetagentseal/founder-playbook724—~2.3kAutomated safety check: PassMIT
B2B Lead Generationminhnv0807/ai-business-skills608—~1.2kAutomated safety check: PassMIT
Google Maps Search API Skillbrowser-act/skills6.1k1 repos~1.6kAutomated safety check: PassMIT

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Questions about List Builder

What does List Builder do?

Prospecting skill for Claude Code and Codex: build a targeted list of B2B prospects or businesses from a natural-language ICP brief using real-time company and contact data. List Builder is an agent skill from explorium-ai/gtm-skills. Prospecting skill for Claude Code and Codex: build a targeted list of B2B prospects or businesses from a natural-language ICP brief using real-time company and contact data.

When should I use List Builder?

List Builder fits situations like: the user asks to build a list; pull a target account list; give me contacts at; show me companies that.

How do I install List Builder in Claude Code?

Run `npx skills add explorium-ai/gtm-skills --skill list-builder -a claude-code`. Or copy the skill folder (skills/list-builder in explorium-ai/gtm-skills) into .claude/skills/list-builder in your project. Claude Code loads it when a task matches its description.

How do I install List Builder in Codex?

Run `npx skills add explorium-ai/gtm-skills --skill list-builder -a codex`. Or copy the skill folder (skills/list-builder in explorium-ai/gtm-skills) into .agents/skills/list-builder in your project. Codex loads it when a task matches its description.

Can I use List Builder in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add explorium-ai/gtm-skills --skill list-builder -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/list-builder, .gemini/skills/list-builder, .github/skills/list-builder and .opencode/skills/list-builder in your project.

What does List Builder need to run?

SKILL.md names no scripts, command-line tools or credentials: List Builder is instructions for the agent only.

Does List Builder access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is List Builder safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does List Builder use?

List Builder is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does List Builder use?

About 1.5k tokens (SKILL.md is roughly 6.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to List Builder?

Skills that share tags, products or a category with List Builder: Google Maps API Skill (browser-act/skills, 6.1k stars), Lead Researcher (borghei/Claude-Skills, 881 stars), 100m Leads (getagentseal/founder-playbook, 724 stars) and B2B Lead Generation (minhnv0807/ai-business-skills, 608 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains List Builder?

explorium-ai (a GitHub organization) maintains it in explorium-ai/gtm-skills, which has 163 GitHub stars. The repository holds 17 skills in this directory. The repository was last updated on September 24, 2026.

Source: explorium-ai/gtm-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.