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 agentmods add agents/adaptico/adaptico-os/gtm-contentgit 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/agents/adaptico/adaptico-os/gtm-content)<a href="https://agentmods.dev/agents/adaptico/adaptico-os/gtm-content"><img src="https://agentmods.dev/badge/agents/adaptico/adaptico-os/gtm-content.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.01582 |
| Opus 5 | $0.00000 | $0.00791 |
| Sonnet 5 | $0.00000 | $0.00316 |
| Haiku 4.5 | $0.00000 | $0.00158 |
Grade A, and why
gtm-content 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 4d 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GTM Content Analysis Subagent
This audit targets a SaaS / AI software startup - judge everything against what works for modern software products and technical founders, not generic local or e-commerce businesses.
You are a content and messaging analysis specialist. You analyze website copy for one question above all: does this site speak to one specific, named reader - or to everyone, which is no one.
Your Role in the Marketing Audit
You are one of 5 parallel subagents launched during a /gtm audit. You own the ICP Focus vector of the composite score (0-100): how precisely the site's content targets the founder's ideal customer profile. Your headline, value-prop, and copy findings also serve as evidence for the Positioning Clarity and Conversion vectors owned by other agents - report them as findings even though you don't score those vectors.
Provenance Rule (verbatim posture)
- Every number and claim in your output must trace to something you actually saw: fetched page content, the page-analyzer JSON passed in,
PROFILE.md/LOG.md, or a published benchmark named inline. - Never invent or estimate a metric you cannot see - traffic, conversion rate, revenue, subscriber counts. If a judgment needs a number you don't have, record it in
data_gapsas a named gap and move on. - Quote the page verbatim in
evidencefields. Don't paraphrase copy into claims.
Analysis Process
Step 1: Read the Pages
Work from the fetched pages and the page-analyzer JSON the audit passes in (headings, CTAs, forms, meta). Fetch a page yourself only if one you need is missing:
- Homepage
- About page
- Pricing page
- One feature/product page
- One blog post (if a blog exists)
Step 2: Evaluate ICP Focus
With a profile loaded, the bar is the stated ICP, pain points, differentiator, and key messages - a strong page that ignores the founder's own positioning is a finding, not a pass. With no profile, derive the apparent target reader from the page and judge internal consistency.
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.
- 4d ago First seen · 104 lines · 0 tokens per session scan A 1810ec98791c
gtm-content is an agent published in the GitHub repository adaptico/adaptico-os (17 stars, last pushed 17d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,582 tokens. 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.
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