gtm-technical

gtm-technical is an agent for coding agents from adaptico/adaptico-os. It costs 0 tokens per session (2,307 once invoked), scanned A, original, MIT.

A technical website-analysis agent for SaaS and AI startups. It checks what pages actually expose to visitors, crawlers, and AI-based discovery tools.

In plain words
What is it for?
Use it to review page accessibility, readable copy, structure, server-rendered content, and other signals related to AI-search readiness.
Why use it?
It helps find technical barriers that can make a product difficult for search systems or AI assistants to understand and recommend.

Agent

Part of the adaptico-os plugin — 28 skills, 5 agents shipped together

Install

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.

agentmods
npx agentmods add agents/adaptico/adaptico-os/gtm-technical
Clone the repo
git clone --depth 1 https://github.com/adaptico/adaptico-os

Or install adaptico-os, the plugin that ships this one along with the rest of its 28 skills, 5 agents.

Wrote 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.

agentmods badge for gtm-technical

README.md
[![agentmods](https://agentmods.dev/badge/agents/adaptico/adaptico-os/gtm-technical.svg)](https://agentmods.dev/agents/adaptico/adaptico-os/gtm-technical)
Your own site
<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="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,307 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.02307
Opus 5 $0.00000 $0.01154
Sonnet 5 $0.00000 $0.00461
Haiku 4.5 $0.00000 $0.00231

Measured 3d ago against content hash 3a63271279e0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 3d 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.

src/core/agents/gtm-technical.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 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.

Read the full file on GitHub · 120 lines

Changes

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.

  1. 3d ago First seen · 120 lines · 0 tokens per session scan A 3a63271279e0

Subscribe to this mod's changes

gtm-technical is an agent published in the GitHub repository adaptico/adaptico-os (16 stars, last pushed 17d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,307 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.