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-channelgit 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-channel)<a href="https://agentmods.dev/skills/adaptico/adaptico-os/gtm-channel"><img src="https://agentmods.dev/badge/skills/adaptico/adaptico-os/gtm-channel/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-channel"><img src="https://agentmods.dev/badge/skills/adaptico/adaptico-os/gtm-channel.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 | $0.00173 | $0.04473 |
| Opus 5 | $0.00086 | $0.02237 |
| Sonnet 5 | $0.00035 | $0.00895 |
| Haiku 4.5 | $0.00017 | $0.00447 |
Grade C, and why
gtm-channel 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 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.
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 — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pick Your Channel - One Compounding Bet
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 (
channel): Tier 1 Too early · Tier 2 Core · Tier 3 Core. If the founder's tier (from PROFILE.md) makes this Too early or Avoid, prepend this note verbatim: "Committing to one distribution channel comes after you've validated demand by hand. Right now the job is unscalable, manual acquisition - sell one user at a time. Force the single-channel pick once manual traction proves people want this." 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 channel-decision engine for /gtm channel <target>. The most common early distribution failure is not picking the wrong channel - it is never really picking one: a bit of posting, a bit of cold email, a half-started blog, each fed too little to ever produce a signal. Five channels at two hours each lose to one channel at ten, because reach in any channel comes from consistency the channel's algorithm or community can trust. This skill exists to end that scatter. It deletes options: the founder arrives with five channels and leaves with one, a dated test, and a written reason for every channel that lost.
The method is a founder-sized implementation of the Bullseye framework from Gabriel Weinberg and Justin Mares's book Traction: list every channel before temperament deletes the interesting ones, run a cheap bounded test on the most promising, and once a channel works, put everything into it - digging deeper in a working channel beats opening a second front. One deliberate deviation, stated openly: the book suggests cheap parallel tests on the two or three most promising channels; at solo-founder capacity, one test run well beats three run badly, so this skill commits to one channel at a time and names the runner-up as the next test if the kill date fires.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 200 lines · 173 tokens per session scan C ea3f6c1ef925
gtm-channel is a skill published in the GitHub repository adaptico/adaptico-os (18 stars, last pushed 23d ago), licensed MIT. It adds 173 tokens to every session and 4,473 once invoked, about $0.0009 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.
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