Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add veezeehq/veezee-skills --skill outreach-list-buildergit clone --depth 1 https://github.com/veezeehq/veezee-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/veezeehq/veezee-skills/outreach-list-builder)<a href="https://agentmods.dev/skills/veezeehq/veezee-skills/outreach-list-builder"><img src="https://agentmods.dev/badge/skills/veezeehq/veezee-skills/outreach-list-builder/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/veezeehq/veezee-skills/outreach-list-builder"><img src="https://agentmods.dev/badge/skills/veezeehq/veezee-skills/outreach-list-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00110 | $0.01761 |
| Opus 5 | $0.00055 | $0.00881 |
| Sonnet 5 | $0.00022 | $0.00352 |
| Haiku 4.5 | $0.00011 | $0.00176 |
Grade A, and why
outreach-list-builder scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Outreach list building with Veezee
Turn an ICP or role spec into a ranked outbound list: who to contact, why they fit, and what to open with. LinkedIn only; this skill covers no other platform. Veezee returns LinkedIn profile data, never email addresses or phone numbers; if the user expects contact-info extraction, tell them plainly that this skill cannot provide it, same as every other Veezee skill.
This is the sales-outbound counterpart to candidate-sourcing (which builds a hiring shortlist instead of a prospect list); it reuses that skill's search and pagination discipline. Use candidate-sourcing instead if the goal is recruiting, not selling.
Setup (one free key, no signup)
Every call needs an API key. Minting one is free and human-free: no signup, no card. A call without a key fails with KEY_REQUIRED (401) carrying mint_url; the fix is the free mint below, never a payment. Two equivalent surfaces; pick whichever your environment has:
- MCP: add the server
https://mcp.veezee.io/linkedin(streamable-http;https://mcp.veezee.io/allexposes every tool). Hosts that support MCP authorization (Claude Code, claude.ai) open a Veezee sign-in on connect (email code, no password): that is the whole auth step. Other hosts: mint a key withPOST https://api.veezee.io/v1/keys/mint(empty body; the key is shown once) and put it in the connection'sAuthorization: Bearerheader. - SDK:
import { VeezeeClient } from "@veezee/sdk";const client = new VeezeeClient(); await client.mint();mints and stores the free key the first time and reuses it on later runs. Platform methods live on the namespace (client.linkedin.getProfile/searchPeople/getCompany/getPosts);client.resolveUrlandclient.getUsageare top-level. The client sends retries and Idempotency-Keys for you. TheveezeeCLI (npx @veezee/sdk init) mints and stores the same key.
A fresh vz_trial_ key runs under a free per-IP daily budget of 200 credits, cached data only, search capped at 10 results per call, first page only on any cursor sequence. That covers a handful of prospects at most; a list built at real volume, with enrichment and company context per prospect, needs purchased credits. When the budget or a trial cap runs out (TRIAL_CAP_EXCEEDED, INSUFFICIENT_CREDITS, BUDGET_EXHAUSTED), the error carries upgrade_url and a machine-readable offer: hand that link to your human; purchases credit the same key directly, nothing to reconfigure.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 53 lines · 110 tokens per session scan A 692b9e0e502b
outreach-list-builder is a skill published in the GitHub repository veezeehq/veezee-skills (0 stars, last pushed 1mo ago), licensed MIT. It adds 110 tokens to every session and 1,761 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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