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-copygit 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-copy)<a href="https://agentmods.dev/skills/adaptico/adaptico-os/gtm-copy"><img src="https://agentmods.dev/badge/skills/adaptico/adaptico-os/gtm-copy/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-copy"><img src="https://agentmods.dev/badge/skills/adaptico/adaptico-os/gtm-copy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00080 | $0.04691 |
| Opus 5 | $0.00040 | $0.02346 |
| Sonnet 5 | $0.00016 | $0.00938 |
| Haiku 4.5 | $0.00008 | $0.00469 |
Grade A, and why
gtm-copy 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 — 393 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Copywriting Analysis & Generation
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 (
copy): Tier 1 Useful · Tier 2 Core · Tier 3 Useful. Appropriate at every served tier - generate with no stage note.
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 copywriting engine for /gtm copy <target>. You analyze existing website copy, score it, and generate optimized alternatives with specific before/after examples. Every recommendation is grounded in proven copywriting frameworks and tailored to the detected business type.
When This Skill Is Invoked
The user runs /gtm copy <target>. Fetch the target page(s), analyze the existing copy, score it, and produce both terminal output and a detailed YYYY-MM-DD-copy-suggestions.md report (see the orchestrator's Project Resolution).
Phase 0: Gather Context
Before fetching anything, run the orchestrator's Project Resolution. With a profile loaded, read PROFILE.md and pull the fields that constrain copy - /gtm init captured them and /gtm position / /gtm competitors may have sharpened them, so don't re-derive from the page what's already here:
- ICP, Secondary audience, Key pain points - who the copy speaks to and the pain it names; these set headline relevance (2.1) and seed the Value Proposition Canvas (2.4).
- Customer Evidence - validated pains, verbatim customer phrases, and switching triggers from real conversations (
/gtm interviewsmaintains it). The strongest language source this skill can get: when present, lead headlines and rewrites with the customers' exact words for the problem and the value instead of inventing phrasing. - Differentiator and Key messages - the positioning every rewrite leads with.
/gtm positionand/gtm competitorswrite these back here socopyinherits them; treat them as the spine of the rewrites, not optional input. - Tone and Avoid - the voice generated copy must honor and the claims it must never make; these outrank the page-derived voice (1.3) on conflict.
brand-voice.md(project root, written by/gtm brand) - when present, the full voice contract: its Words We Use / Words We Avoid, Do/Don't rules, and one-line rule govern every rewrite. It outranks both the profile's one-lineToneand the page-derived voice.- Project type, Stage, and Main goal - frame the read; a Tier 1 founder needs copy that wins a first persona, not category-defining prose.
- Then run the Competitor Resolution Protocol for the differentiation angle, and read any
YYYY-MM-DD-positioning.mdorYYYY-MM-DD-competitor-report.mdin the folder for detail.
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 · 393 lines · 80 tokens per session scan A a146a2ef3396
gtm-copy is a skill published in the GitHub repository adaptico/adaptico-os (18 stars, last pushed 22d ago), licensed MIT. It adds 80 tokens to every session and 4,691 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 2026-08-30.
Other skills, from other repositories
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.
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.
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-landing
Audit paid-ad landing pages for message match, mobile experience, performance, accessibility, trust, forms, consent, tracking, security, and conversion friction. Use for landing-page audit, post-click experience, LP audit, conversion-rate optimization, form optimization, ad-to-page message match, redirects, blocked…