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-post-generatorgit 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-post-generator)<a href="https://agentmods.dev/skills/first-touch-inc/firsttouch-agent-skill-packs/founder-post-generator"><img src="https://agentmods.dev/badge/skills/first-touch-inc/firsttouch-agent-skill-packs/founder-post-generator/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-post-generator"><img src="https://agentmods.dev/badge/skills/first-touch-inc/firsttouch-agent-skill-packs/founder-post-generator.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 | $0.00088 | $0.01401 |
| Opus 5 | $0.00044 | $0.00700 |
| Sonnet 5 | $0.00018 | $0.00280 |
| Haiku 4.5 | $0.00009 | $0.00140 |
Grade A, and why
founder-post-generator 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 9d 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Founder Post Generator
Outcome: A steady stream of founder-voice LinkedIn posts that create the engagement the rest of this pack harvests. Posts feed Social Engagement monitoring; engagers feed warm-engager-followup; conversations feed pipeline. This skill drafts - the founder posts from their own account.
First-run note
This skill sends nothing and uses no daily send budget. Before the first run, capture two things (reuse them every run):
- Founder voice profile: 2-3 sample posts or messages the founder actually wrote, plus tone rules - phrases they use, phrases they hate, formality level, topics they will not touch. Save this as a reusable profile: restate it in the first run's output so the founder can keep it (notes file, saved prompt, agent memory). On every later run, if a profile exists, confirm "still accurate?" and reuse it - never make the founder re-explain their voice. Re-calibrate when a draft sounds off or roughly monthly.
- Audience: who should engage (the ICP from
../../references/onboarding.md). A post that attracts the wrong engagers creates busywork downstream.
When to use
- "What should I post this week?"
- Post engagement is thin and the warm-engager play has nothing to harvest
- Before launching Social Engagement monitoring on the founder's own profile
- A customer win, product lesson, or strong opinion is sitting unused
Step-by-step
1. Collect raw material
Ask for whichever exists - one strong input beats five weak ones:
- A recent customer conversation, win, or objection that surprised the founder
- A market observation ("everyone is doing X, we keep seeing Y")
- A build-in-public moment: something shipped, broken, learned, or changed
- A strong opinion the founder actually holds and will defend in comments When HubSpot is connected, closed-won stories and common deal objections are good seeds - but never use customer names or details without explicit approval.
2. Pick the post type
Five types, rotate across the week - do not post the same shape twice in a row:
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.
- 9d ago First seen · 87 lines · 88 tokens per session scan A 45de4bad65a5
founder-post-generator 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 88 tokens to every session and 1,401 once invoked, about $0.0004 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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