gtm-prospecting-desk · v0.2.0 · 2026-09-22 · sha256 2bda7d2ff5ac2d94

gtm-prospecting-desk v0.2.0A

Immutable. This exact content never changes and is served at /api/v1/blob/2bda7d2ff5ac2d94.

---
name: gtm-prospecting-desk
description: This skill should be used when the user wants to run the Outbound Pipeline Engine skill, or asks to "build my prospecting pipeline", "run my outbound research", "keep a prospect table current", or wants recurring ICP-filtered company and people discovery with scored rows and outreach drafts. Runs on the superagnt MCP: first-party people/company data + LinkedIn + workspace database. Drafts only — sending is always the human's.
version: 0.2.0
---

# Outbound Pipeline Engine

Outbound research end to end, compounding in one pipeline table. This skill
builds on the base `lead-generation` skill's workflow — read that one for the
per-step tool detail; this one adds the standing-desk structure.

## Step 0 — tools

`agnt_tools_list_enabled`; if missing:
`agnt_tools_enable({ "families": ["data:linkedin", "database"] })` (the
first-party `data_agnt_*` people/company tools are always on).
`requires_upgrade` → `confirm_url` to the user → wait → re-run. (The
gtm-prospecting-desk skill endpoint pre-enables these.)

## Step 1 — pin the ICP (first run only)

Company filters (size, industry, geography, signals) + buyer titles + any
disqualifiers, into `icp_profile` (`agnt_db_insert`). Create
`prospects(id, company, company_domain, person, title, linkedin_url, email,
email_verified boolean, fit_score int, fit_reason text, status text,
draft text, updated_at timestamptz)` — upsert key (person, company_domain).

## Step 2 — the desk run

1. `data_agnt_companies_search` against the ICP filters (or
`data_agnt_companies_discover` for similar-to expansion); skip companies
already in the table unless refreshing.
2. `data_agnt_people_search` per company for the buyer titles;
`data_agnt_people_enrich` on the chosen person; `data_linkedin_*` for
profile detail when the LinkedIn family is enabled.
3. `data_agnt_people_email_finder` then ALWAYS
`data_agnt_people_email_verifier`. Unverified rows keep
`email_verified=false` — they stay workable via LinkedIn.
4. `agnt_db_upsert` every row with `status` transitions
(new → enriched → scored → drafted) so a failed run resumes instead of
restarting.
5. Score each row (fit_score + one-line fit_reason from the ICP), then write
outreach drafts into `draft` for the top rows — the user's voice (ask for
two past emails once, store the voice notes in `icp_profile`).

## Step 3 — report

From the table: counts by status, the top 10 by fit with reasons, and where
the drafts are. Numbers come from `agnt_db_select`, never memory.

## Step 4 — offer the standing desk (a task agent)

After one successful run: offer a scheduled refresh (weekly beats daily for
prospecting) by building a task agent — recipe in the base `task-agents`
skill. `agnt_agents_create` with a system prompt carrying step 2 verbatim
(ICP table, pipeline table, status transitions), only the tools it uses,
deploy, then `agnt_schedules_create`; cadence confirmed with the user,
billed runs stated plainly, module trials via `confirm_url` on
`requires_upgrade`. 500+ row enrichment belongs in a data job (see
data-pipelines) rather than a longer session.

## Hard rules

- **Drafts only. This skill never sends email, LinkedIn messages, or
anything else.** Wiring a sending tool is the user's own deliberate act.
- Respect disqualifiers in `icp_profile` absolutely — a disqualified company
never re-enters the pipeline.