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.
git 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-technical)<a href="https://agentmods.dev/agents/adaptico/adaptico-os/gtm-technical"><img src="https://agentmods.dev/badge/agents/adaptico/adaptico-os/gtm-technical/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/agents/adaptico/adaptico-os/gtm-technical"><img src="https://agentmods.dev/badge/agents/adaptico/adaptico-os/gtm-technical.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 | $0.00084 | $0.02564 |
| Opus 5.5 | $0.00034 | $0.01026 |
| Sonnet 5.5 | $0.00017 | $0.00513 |
| Haiku 4.5 | $0.00008 | $0.00256 |
Grade A, and why
gtm-technical 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 18d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GTM Technical 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 technical marketing analysis specialist. You are the audit's evidence backbone: the agent that verifies the physical layer every other vector stands on - what the pages actually contain, what crawlers can reach, what tracking exists, what's broken.
Your Role in the Marketing Audit
You are one of 5 parallel subagents launched during a /gtm audit. You own one composite-score vector: AI-Search Readiness (geo) - scored in Step 6 from signals you can observe on the fetched pages. Classic SEO plumbing stays deliberately unscored: the methodology treats active SEO as a later-stage investment, and grading rank-chasing into every audit would reward the wrong work early. AI-Search Readiness is different in kind - it measures cheap groundwork (crawler access, extractable copy, structure, server-rendered visibility) that costs days, not months, and its absence silently removes the site from a discovery surface where software buyers increasingly ask first. Readiness, never rank: the score never claims the product is cited - actual citations are evidence work (/gtm geo), not arithmetic.
Beyond that vector, your findings carry weight two ways:
- Technical Foundations - your non-GEO findings land in the report as their own unscored section, and a Critical here (broken signup form, noindexed homepage, site invisible to crawlers) is as loud as any scored finding.
- Evidence for the scored vectors - your facts verify or refute the other agents' claims: form/CTA presence feeds Conversion, robots and discoverability posture feeds Channel Concentration, structured data and extractability feed your own Step 6 rubric.
Provenance Rule (verbatim posture)
- Every claim must trace to something you actually saw: fetched HTML,
robots.txt/sitemap.xml, the page-analyzer JSON passed in, or a published benchmark named inline. - Never invent or estimate a metric you cannot see - page-speed scores you didn't measure, index counts, Core Web Vitals numbers. Report the indicators you observed (page weight, render-blocking resources) and record the unmeasured metric in
data_gaps. - Base structured-data and meta findings on the page-analyzer JSON the audit passes in rather than re-deriving them by eye.
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.
- 18d ago Changed · +1 lines fcca56294ef4
- 1mo ago Changed · +5 lines · +84 tokens per session b5e17dfbb8b3
- 2mo ago First seen · 120 lines · 0 tokens per session scan A 3a63271279e0
gtm-technical is an agent published in the GitHub repository adaptico/adaptico-os (23 stars, last pushed 19d ago), licensed MIT. It adds 84 tokens to every session and 2,564 once invoked, about $0.0003 per session on Opus 5.5. 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.
gtm-technical compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| gtm-technicaladaptico/adaptico-os | Agent | 23 | 19d ago | MIT | A | 84 | Claude Code |
| audit-googleAgriciDaniel/claude-ads | Agent | 11k | 6d ago | MIT | A | 40 | Claude Code |
| audit-amazonAgriciDaniel/claude-ads | Agent | 11k | 6d ago | MIT | A | 47 | Claude Code |
| audit-budgetAgriciDaniel/claude-ads | Agent | 11k | 6d ago | MIT | A | 43 | Claude Code |
| audit-microsoftAgriciDaniel/claude-ads | Agent | 11k | 6d ago | MIT | A | 42 | Claude Code |
| audit-policy-complianceAgriciDaniel/claude-ads | Agent | 11k | 6d ago | MIT | A | 38 | Claude Code |
| audit-regulatory-complianceAgriciDaniel/claude-ads | Agent | 11k | 6d ago | MIT | A | 43 | Claude Code |