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/rajitsaha/100xprismWrote 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/rules/rajitsaha/100xprism/programmatic-seo)<a href="https://agentmods.dev/rules/rajitsaha/100xprism/programmatic-seo"><img src="https://agentmods.dev/badge/rules/rajitsaha/100xprism/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/rules/rajitsaha/100xprism/programmatic-seo"><img src="https://agentmods.dev/badge/rules/rajitsaha/100xprism/programmatic-seo.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 | $0.00031 | $0.01392 |
| Opus 5 | $0.00015 | $0.00696 |
| Sonnet 5 | $0.00006 | $0.00278 |
| Haiku 4.5 | $0.00003 | $0.00139 |
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 5d 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 — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Programmatic SEO
Build template- and data-driven SEO pages at scale that rank, provide value, and avoid thin-content penalties.
Initial Assessment
Product context: If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md in older setups), read it first and tailor output to it; only ask for what it doesn't cover.
Understand first:
- Business Context — product/service? Target audience? Conversion goal for these pages?
- Opportunity — what search patterns exist? How many potential pages? Search volume distribution?
- Competition — who ranks now? What do their pages look like? Can you realistically compete?
Core Principles
- Unique value per page — value specific to that page, not just swapped variables in a template; the more differentiated, the better.
- Proprietary data wins — data defensibility hierarchy: (1) proprietary (you created it), (2) product-derived (from your users), (3) user-generated (your community), (4) licensed (exclusive access), (5) public (anyone can use—weakest).
- Clean URL structure — use subfolders, not subdomains; subfolders consolidate domain authority, subdomains split it. Good:
yoursite.com/templates/resume/. Bad:templates.yoursite.com/resume/. - Genuine search intent match — pages must actually answer what people search for.
- Quality over quantity — better 100 great pages than 10,000 thin ones.
- Avoid Google penalties — no doorway pages, keyword stuffing, or 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 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.
- 5d ago First seen · 161 lines · 31 tokens per session scan A a3101a4d9743
programmatic-seo is a cursor rule published in the GitHub repository rajitsaha/100xprism (10 stars, last pushed 8d ago), licensed MIT. It adds 31 tokens to every session and 1,392 once invoked, about $0.0002 per session on Opus 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 2026-09-03.
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