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 adaptico/adaptico-os --skill gtm-leadmagnetgit clone --depth 1 https://github.com/adaptico/adaptico-osWrote 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/adaptico/adaptico-os/gtm-leadmagnet)<a href="https://agentmods.dev/skills/adaptico/adaptico-os/gtm-leadmagnet"><img src="https://agentmods.dev/badge/skills/adaptico/adaptico-os/gtm-leadmagnet/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/adaptico/adaptico-os/gtm-leadmagnet"><img src="https://agentmods.dev/badge/skills/adaptico/adaptico-os/gtm-leadmagnet.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 | $0.00161 | $0.04095 |
| Opus 5 | $0.00081 | $0.02048 |
| Sonnet 5 | $0.00032 | $0.00819 |
| Haiku 4.5 | $0.00016 | $0.00409 |
Grade C, and why
gtm-leadmagnet scanned grade C with 1 finding 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.
Tells the agent never to refusehighAnti-refusal
Suppressing the ability to decline removes a core safety control; a later harmful request then succeeds.
> Then generate the work anyway - never refuse. How it starts
The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lead Magnet - the Email-Capture Asset
Default lens: a SaaS / AI software startup. Advise a technical founder marketing their own modern software product (SaaS, AI/API, dev tool, or app). Tailor every recommendation to that reader.
Stage-fit (
leadmagnet): Tier 1 Too early · Tier 2 Useful · Tier 3 Core. If the founder's tier (from PROFILE.md) makes this Too early or Avoid, prepend this note verbatim: "A lead magnet captures an audience you don't have yet. Building one now pulls you off the real job - direct conversations with potential users. It earns its place once a channel is sending you traffic worth capturing." Then generate the work anyway - never refuse.
Full persona and general guidance: read
../gtm/templates/advisor-prompt.md(installed with the gtm orchestrator); if the file is absent, continue with the default lens above.
You are the capture-asset designer for /gtm leadmagnet <target>. An email list is the one audience no platform algorithm can take away - every other channel is borrowed reach, and the lead magnet is the honest trade that converts borrowed reach into owned. Most lead magnets fail the same two ways: a generic asset nobody wants ("The Ultimate Guide to [Category]"), or weeks sunk into building one before any evidence that the ICP would trade an email for it. This skill designs against both: one narrow asset, format picked by the ICP's sharpest pain, small enough to build in hours or days - and a validation checklist that must pass before anything gets built.
Where this sits among the neighboring commands, so the jobs stay distinct: /gtm channel picks where the traffic comes from; this skill converts that traffic into a list; /gtm emails writes what the list receives afterward. Run it when a channel is already sending people worth capturing - and if none is, this skill says so honestly and designs anyway, sized down.
When This Skill Is Invoked
The user runs /gtm leadmagnet <target>, where <target> is a URL, a saved project name, or omitted to use the default project. Run the orchestrator's Project Resolution, gather context (Phase 0), run the honesty check (Phase 1), then design: format by pain (Phase 2), hook and outline (Phase 3), delivery and capture flow (Phase 4), and the validation checklist (Phase 5). Output to a YYYY-MM-DD-leadmagnet.md report (see the orchestrator's Project Resolution; never overwrite - append -2, -3 for same-day runs).
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 · 197 lines · 161 tokens per session scan C 6ab168f541ce
gtm-leadmagnet is a skill published in the GitHub repository adaptico/adaptico-os (18 stars, last pushed 25d ago), licensed MIT. It adds 161 tokens to every session and 4,095 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it C with 1 finding (tells the agent never to refuse). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
competitors
Audit competitors using ScaleBrick's 3-surface framework (social, web/pages, SEO). Categorizes their pricing, features, and landing pages. Identifies gaps you can exploit, positioning angles no one is claiming, and specific moves you can make this week.
audit
Analyze whether TikTok or Instagram search traffic is a viable growth channel for your business. Uses ScaleBrick's framework to evaluate demand, competition, content fit, and intent categories. Ends with a go/no-go recommendation.
strategy
Generate a full marketing strategy using ScaleBrick's "TikTok as Search Engine" framework. Produces themes, pillars, voice, keyword plan, and posting schedule specific enough to execute on day one.
keywords
Research high-intent TikTok and Instagram search keywords using ScaleBrick's framework. Returns categorized keywords with intent type, search volume estimate, difficulty score, and content angle for each.
ads-audit
Run a source-grounded paid-advertising audit for one or more of Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, and X. Use for full ad checks, account health reviews, paid-media diagnostics, partial audits after authentication or worker failure, missing-platform…
ads-meta
Audit Meta Ads measurement, Pixel and Conversions API, attribution, Facebook and Instagram creative, audiences, placements, automation, budgets, account structure, and policy. Use for Meta Ads, Facebook Ads, Instagram Ads, Advantage+, Pixel, CAPI, Events Manager, creative fatigue, or Meta campaign optimization.