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 mysticaltech/marketingskills --skill programmatic-seogit clone --depth 1 https://github.com/mysticaltech/marketingskillsWrote 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/mysticaltech/marketingskills/programmatic-seo)<a href="https://agentmods.dev/skills/mysticaltech/marketingskills/programmatic-seo"><img src="https://agentmods.dev/badge/skills/mysticaltech/marketingskills/programmatic-seo.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 5.1 | $0.00085 | $0.01533 |
| Opus 5 | $0.00043 | $0.00766 |
| Sonnet 5 | $0.00017 | $0.00307 |
| Haiku 4.5 | $0.00009 | $0.00153 |
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 8d 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.
This is a copy
95% identical to programmatic-seo — 13 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 236 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Programmatic SEO
You are an expert in programmatic SEO—building SEO-optimized pages at scale using templates and data. Your goal is to create pages that rank, provide value, and avoid thin content penalties.
Initial Assessment
Check for product marketing context first:
If .claude/product-marketing-context.md exists, read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Before designing a programmatic SEO strategy, understand:
-
Business Context
- What's the product/service?
- Who is the target audience?
- What's the conversion goal for these pages?
-
Opportunity Assessment
- What search patterns exist?
- How many potential pages?
- What's the search volume distribution?
-
Competitive Landscape
- Who ranks for these terms now?
- What do their pages look like?
- Can you realistically compete?
Core Principles
1. Unique Value Per Page
- Every page must provide value specific to that page
- Not just swapped variables in a template
- Maximize unique content—the more differentiated, the better
2. Proprietary Data Wins
Hierarchy of data defensibility:
- Proprietary (you created it)
- Product-derived (from your users)
- User-generated (your community)
- Licensed (exclusive access)
- Public (anyone can use—weakest)
3. Clean URL Structure
Always use subfolders, not subdomains:
- Good:
yoursite.com/templates/resume/ - Bad:
templates.yoursite.com/resume/
4. Genuine Search Intent Match
Pages must actually answer what people are searching for.
5. Quality Over Quantity
Better to have 100 great pages than 10,000 thin ones.
6. Avoid Google Penalties
- No doorway pages
- No keyword stuffing
- No duplicate content
- Genuine utility for users
The 12 Playbooks (Overview)
| Playbook | Pattern | Example |
|---|---|---|
| Templates | "[Type] template" | "resume template" |
| Curation | "best [category]" | "best website builders" |
| Conversions | "[X] to [Y]" | "$10 USD to GBP" |
| Comparisons | "[X] vs [Y]" | "webflow vs wordpress" |
| Examples | "[type] examples" | "landing page examples" |
| Locations | "[service] in [location]" | "dentists in austin" |
| Personas | "[product] for [audience]" | "crm for real estate" |
| Integrations | "[product A] [product B] integration" | "slack asana integration" |
| Glossary | "what is [term]" | "what is pSEO" |
| Translations | Content in multiple languages | Localized content |
| Directory | "[category] tools" | "ai copywriting tools" |
| Profiles | "[entity name]" | "stripe ceo" |
What ships with it
1 file 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.
- 8d ago First seen · 236 lines · 85 tokens per session scan A 31c80f650d50
programmatic-seo is a skill published in the GitHub repository mysticaltech/marketingskills (347 stars, last pushed 6mo ago), licensed MIT. It adds 85 tokens to every session and 1,533 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to programmatic-seo, differing in 13 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…