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 First-Touch-Inc/firsttouch-agent-skill-packs --skill founder-led-outboundgit clone --depth 1 https://github.com/First-Touch-Inc/firsttouch-agent-skill-packsWrote 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/first-touch-inc/firsttouch-agent-skill-packs/founder-led-outbound)<a href="https://agentmods.dev/skills/first-touch-inc/firsttouch-agent-skill-packs/founder-led-outbound"><img src="https://agentmods.dev/badge/skills/first-touch-inc/firsttouch-agent-skill-packs/founder-led-outbound/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/first-touch-inc/firsttouch-agent-skill-packs/founder-led-outbound"><img src="https://agentmods.dev/badge/skills/first-touch-inc/firsttouch-agent-skill-packs/founder-led-outbound.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 | $0.00094 | $0.02318 |
| Opus 5 | $0.00047 | $0.01159 |
| Sonnet 5 | $0.00019 | $0.00464 |
| Haiku 4.5 | $0.00009 | $0.00232 |
Grade A, and why
founder-led-outbound 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 10d 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Founder-Led AI SDR
Outcome: Produce a daily approval-ready batch of founder-voice LinkedIn touches from either an existing HubSpot/contact list or a newly discovered ICP list, without requiring HubSpot to start.
First-run onboarding gate
Before running this skill for the first time in a workspace, load ../../references/onboarding.md and complete the onboarding questions. Do not proceed until you know: LinkedIn account type (free/basic = no connection notes; recommend 10 connection requests/day and never exceed the FirstTouch max of 20/day; Sales Navigator/Premium = connection notes available; recommend 20 connection requests/day and never exceed the FirstTouch max of 30/day), HubSpot access (MCP, service key/private app token, HubSpot list only, or none), and which play the user wants to run. For founders, recommend the social engagement flow first when a monitored profile or engager list exists. If no engager source is available right now, this play is the immediate fallback and can run by building a new ICP list with FirstTouch Discover Contacts without HubSpot.
When to use
- "I'm the founder, help me do my own outbound"
- "Run AI SDR, but make it sound like me"
- Founder-led growth / founder-mode GTM
- Strategic accounts where the founder's voice matters
- Booking meetings from the founder's network, post engagement, or a newly discovered ICP list
When NOT to use
- High-volume SDR outbound where the founder will not personally approve the queue
- Outreach from a sender who is not authorized to use the founder's LinkedIn seat
- Generic blasts with weak personalization or no real signal
What makes founder AI SDR different
Founder-led AI SDR is the same motion as AI SDR, but with a founder lens:
- Lower volume, higher taste bar - every row must feel worthy of the founder's name.
- Founder voice - brief, direct, specific, and free of SDR-speak.
- Real signal first - post engagement, company change, role context, mutual connection, or a clear ICP reason.
- Daily approval queue - the agent drafts; the founder approves; FirstTouch executes.
- No HubSpot required to start - if there is no HubSpot list, use FirstTouch Discover Contacts from the founder's ICP.
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.
- 10d ago First seen · 151 lines · 94 tokens per session scan A 0c21847ee182
founder-led-outbound is a skill published in the GitHub repository First-Touch-Inc/firsttouch-agent-skill-packs (5 stars, last pushed 2mo ago), licensed MIT. It adds 94 tokens to every session and 2,318 once invoked, about $0.0005 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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