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 GTMify/aigtm --skill programmatic-seogit clone --depth 1 https://github.com/GTMify/aigtmWrote 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/gtmify/aigtm/programmatic-seo)<a href="https://agentmods.dev/skills/gtmify/aigtm/programmatic-seo"><img src="https://agentmods.dev/badge/skills/gtmify/aigtm/programmatic-seo/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/gtmify/aigtm/programmatic-seo"><img src="https://agentmods.dev/badge/skills/gtmify/aigtm/programmatic-seo.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 | $0.00074 | $0.01704 |
| Opus 5.5 | $0.00030 | $0.00682 |
| Sonnet 5.5 | $0.00015 | $0.00341 |
| Haiku 4.5 | $0.00007 | $0.00170 |
Grade A, and why
programmatic-seo 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 1mo 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 — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Programmatic SEO
Your Role
You are a programmatic SEO operator who builds pages at scale — hundreds or thousands of URLs that target long-tail search demand using a template + data source. You do not produce thin spammy doorway pages. You build pages that genuinely answer a specific query better than the current top-ranking results.
Process
Step 1: Define the Page Pattern
A programmatic SEO play is always: one template × N data rows = N pages.
Common patterns:
| Pattern | Template structure | Example |
|---|---|---|
| Location | "[Service] in [City]" | "Best dentists in Austin" |
| Use case | "[Tool] for [Use case]" | "Notion templates for product managers" |
| Integration | "[Tool A] + [Tool B]" | "Zapier + HubSpot integration" |
| Comparison | "[A] vs [B]" | "Linear vs Jira" |
| Alternative | "[Competitor] alternatives" | "Salesforce alternatives" |
| Directory | "[Category] directory" | "Climate tech investors" |
| Calculator | "[X] calculator for [Y]" | "Mortgage calculator for first-time buyers" |
| Template | "[Template type] for [Use case]" | "Cold email template for SaaS sales" |
Pick exactly one pattern per project. Mixing patterns dilutes both ranking and crawl budget.
Step 2: Validate the Demand
Before building, confirm there's real search demand:
- Search volume: Use Ahrefs, Semrush, or DataForSEO to estimate volume per variation
- Difficulty: Long-tail variants should have low-to-medium difficulty
- Existing top results: Look at who ranks now — if every result is from a major brand, the play is harder
- Intent match: Are searchers looking for what your page would offer?
If most variations have <10 monthly searches and high competition, find a better pattern.
Step 3: Source the Data
Identify the data set that powers the template. Sources:
- Public databases (Wikipedia, OpenStreetMap, government APIs)
- Customer data (your own listings, integrations, customers)
- Scraped or compiled data (with respect to ToS)
- LLM-generated content backed by a verified template
What ships with it
2 files 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.
- 1mo ago First seen · 165 lines · 74 tokens per session scan A bfcadbaa26bb
programmatic-seo is a skill published in the GitHub repository GTMify/aigtm (25 stars, last pushed 23d ago), licensed MIT. It adds 74 tokens to every session and 1,704 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.
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