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 agentmods add skills/nowork-studio/notfair-plugin/programmatic-seonpx skills add nowork-studio/notfair-plugin --skill programmatic-seogit clone --depth 1 https://github.com/nowork-studio/notfair-pluginWrote 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/nowork-studio/notfair-plugin/programmatic-seo)<a href="https://agentmods.dev/skills/nowork-studio/notfair-plugin/programmatic-seo"><img src="https://agentmods.dev/badge/skills/nowork-studio/notfair-plugin/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 | $0.00228 | $0.00938 |
| Opus 5 | $0.00114 | $0.00469 |
| Sonnet 5 | $0.00046 | $0.00188 |
| Haiku 4.5 | $0.00023 | $0.00094 |
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 4d 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Programmatic SEO
You are a programmatic-SEO strategist. Your job is to help build (or fix) a large set of template-generated pages that actually rank — not a thin-content farm that earns a manual action. The line between "valuable scaled content" and "spam" is unique value per page; everything here defends that line.
Credit: capability inspired by the open-source
claude-seoproject (MIT, Agrici Daniel). Implementation is original to NotFair.
Step 0 — Scope
Determine the mode:
- Plan — user wants to design a new programmatic set. Collect the query pattern, the data source (spreadsheet/API/DB), and the page count.
- Audit — pages already exist. Collect the URL pattern and sample URLs.
Phase 0 — Preflight & data
Read and follow ../shared/preamble.md. If GSC connected and pages exist, pull
Index coverage (how many of the set are indexed vs. "Crawled/Discovered – not
indexed" — the classic programmatic failure signal) and which patterns get clicks.
Phase 1 — Demand validation
- Does the query pattern have real, distributed search demand across the
variables? (Use
/keyword-researchfor volume.) Generating pages for queries nobody searches is wasted crawl budget. - Estimate addressable patterns vs. patterns worth publishing — not every combination deserves a page.
Phase 2 — Uniqueness & value threshold (pass/fail gate)
For the template, verify each page can carry genuinely unique, useful content:
- Unique data per page (real stats/inventory/specifics), not just the variable swapped into otherwise-identical boilerplate.
- A minimum value bar: would this page help a user who landed on it cold? If a page is just "{city}" find-replaced, it's a doorway page — Google will deindex the set. State this bluntly if the plan fails the bar.
- Plan for the long tail of empty pages (combinations with no data): noindex or don't generate them.
Phase 3 — Architecture
- Internal linking / hubs — pages must be reachable and interlinked (hub pages per category, related-page modules), not orphaned.
- Indexation management — publish high-value pages;
noindexthin ones; submit via sitemap in batches and watch indexation before scaling further. - URL pattern, titles, H1s, and meta templated but de-duplicated.
- Render — ensure content is in the HTML / properly rendered, not client-only.
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.
- 4d ago First seen · 80 lines · 228 tokens per session scan A 90cde0e1a3e7
programmatic-seo is a skill published in the GitHub repository nowork-studio/notfair-plugin (3,447 stars, last pushed 5d ago), licensed MIT. It adds 228 tokens to every session and 938 once invoked, about $0.0011 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 2026-08-30.
Other skills, from other repositories
domscribe
Work with Domscribe — the pixel-to-code bridge. Use when setting up, initializing, or configuring Domscribe for a project, OR when editing or modifying UI components (React, Vue, Next.js, Nuxt), implementing features from captured UI annotations, querying runtime context for source locations, exploring component…
forge-connector
Guides building and deploying Atlassian Forge Teamwork Graph connector apps that ingest external data into Atlassian's Teamwork Graph, making it searchable in Rovo Search and surfaced in Rovo Chat. Use when the user wants to build a Forge connector, ingest external data into Atlassian, connect a third-party tool (e.g.…
forge-cost-optimizer
Optimizes Atlassian Forge apps to reduce platform consumption and avoid unnecessary costs using Atlassian's "Optimise Forge platform costs" guidance. Use when the user asks to optimize Forge app costs, reduce Forge invocations, lower GB-seconds, reduce storage or log usage, tune memory, replace polling, improve…
forge-app-review
Performs a lightweight pre-release readiness review of Atlassian Forge apps across manifest/module wiring, architecture, runtime compatibility, dependency posture, tests, deploy readiness, and obvious security, cost, or reliability smells. Use when the user asks "review my Forge app", "pre-deploy check", "is this app…
logic-review
Find logic bugs in a single file or function via semi-formal execution tracing (Premises → Trace → Divergence → Trigger → Remedy). Trigger when a user shares code and suspects something is wrong without naming a concrete failure — phrases like "review this", "does this look right", "check this function", "audit this…
run-iteration-eval
Run the Logic-Lens content-eval pipeline for one iteration and produce a scored summary.json — use to measure a skill change. Wraps scripts/run-content-evals.sh (runner, costs tokens) and scripts/grade-iteration.py (grader, free, re-runnable). ALWAYS sync the plugin cache first. Use when the user wants to "run the…