00-gtm-router
Plan and run the full API-first GTM chain - the orchestrator (step 00) that turns an ICP description plus optional budget, volume, and urgency into the right…
The packaged cold-start campaign workflow - takes an owner with no list, no CRM, and no outbound history from a plain-English business description to an approved campaign sheet in one supervised pass: business context, a proposed source of record (a public directory - registry,
$ npx -y skills add Zevenue/headless-gtm --skill run-first-campaign --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/run-first-campaignContext preview
The summary Claude sees to decide when to auto-load this skill.
The packaged cold-start campaign workflow - takes an owner with no list, no CRM, and no outbound history from a plain-English business description to an approved campaign sheet in one supervised pass: business context, a proposed source of record (a public directory - registry,
name: run-first-campaign description: > The packaged cold-start campaign workflow - takes an owner with no list, no CRM, and no outbound history from a plain-English business description to an approved campaign sheet in one supervised pass: business context, a proposed source of record (a public directory - registry, professional college, trade association, marketplace, Maps - for local or licensed businesses, or a firmographic pull - 01-prospeo-discover, 01-prospeo-lookalike, 04-theirstack-jobs - for B2B), free ICP qualification, signal ranking, a drafted 3-email sequence, and a HubSpot-import-shaped CSV. Use when someone says "first campaign", "never run a campaign", "no CRM", "I need customers but have nothing to analyze", or wants outbound started from zero existing data. Nothing sends - the deliverables are drafts and files, and every paid step is cost-approved before it runs. For a campaign on an existing list or CRM data, use 00-gtm-router directly.
The cold-start workflow: an owner or founder with no list, no CRM, and no campaign history, taken from "here's my business" to an approved campaign sheet. It chains existing skills in a fixed order with an explicit owner approval between steps. Nothing in this repo sends email - the end state is a drafted 3-email sequence plus a campaign sheet (owner-readable Markdown and a HubSpot-import-shaped CSV) the owner approves on screen.
Chain mechanics follow the router's conventions: each component skill runs by its own SKILL.md, writes into `./runs/` under its own step-prefixed run-id, and hands `records.jsonl` to the next step by explicit path.
Check for `context/offer.md` and `context/icp.md`. If both exist, summarize them in two sentences and confirm they still describe the business. If either is missing, offer two paths: the closest vertical preset from `reference/presets/` (fastest - adopt the archetype, then adjust it together) or the full `gtm-context` interview. Write the result to `context/`. Wait for the owner to confirm the context before anything else runs.
Where these buyers are already listed depends on the ICP. Read the confirmed context and propose the matching source, by name:
dealerships, brokerages, restaurants) live in a public directory - a licensing registry, a professional college, a trade-association "find a member" directory, a marketplace, with 02-apify-maps-discover as the fallback when no structured source exists. These extract via 03 (below).
directory to scrape - the buyer is defined by what the company is. Pull the list instead: 01-prospeo-discover for an ICP-filtered pull, 01-prospeo-lookalike when the owner can name a few good-fit companies, or 04-theirstack-jobs when a hiring signal defines the buyer.
Offer 2-3 candidate sources with a one-line reason each; the owner picks or corrects. Don't open by asking the owner to supply URLs, and don't pull or extract anything before they confirm the source and the cost.
On confirmation, run the matching source skill. For a directory, that is 03-firecrawl-research extract mode with the listing-row schema (03's "Directory and registry extraction" section). Firecrawl bills extraction by tokens (1 credit = 15 tokens), so cost scales with page size: extract the first listing page alone, read the actual charge, and use it as the per-page figure before extracting the rest. For a firmographic pull, that is the discovery skill's own metered call. Either way, state the cost estimate first, follow the source skill's own confirmation thresholds, report the result (N records, credits used), and wait for an acknowledgment before Step 3.
Run 01-icp-qualify on the extracted records against the confirmed context. This step costs nothing. Report the counts - N qualified, M uncertain, K disqualified - and ask 01's uncertain-gate question: forward the uncertain rows too, or hold them? Wait for the answer.
Run 05-signal-builder with the vertical-smb calibration on the qualified set: targets ranked, one angle per account, verbatim provenance on every signal. Present the top targets and the segment pattern; wait for the owner to approve the top segment before anything gets written.
Run email-writer for the approved segment: a 3-email sequence built on the top signals and the fallback angle. Drafts only - present them for edits and wait for "drafts approved" before building the sheet.
Run 07-campaign-sheet on the final `records.jsonl`: `campaign-sheet.md` (who to contact first and why, signal and approach per row) plus `campaign-sheet.csv` with HubSpot default import headers. Present both and stop - nothing is send-ready until the owner approves the sheet on screen.
Optional branch, only when the owner wants send-ready addresses: run 06-resolution-email-person on the approved rows (cost-gated - state the estimate first), then regenerate the sheet with the email column filled.
send it", say that plainly and point at the approved sheet and drafts.
estimate before running; anything above the approved line stops and re-asks.
offer the no-key path (a smaller manual pull, or qualify / rank / write on whatever data already exists).
End the run with a one-paragraph recap: the source of record used, N found -> M qualified, the top 3 tar
GTM without the SaaS layer. An outbound pipeline built as agent skills for Claude Code and Codex: describe an ICP in plain English and the chain takes it from company discovery to verified, signal-ranked contacts - every step running on raw vendor APIs, not
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