Borrowing it
Nothing to install: this file belongs to prashishh/seo-geo-report-engine. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/prashishh/seo-geo-report-engine/main/.agents/skills/programmatic-seo/SKILL.mdgit clone --depth 1 https://github.com/prashishh/seo-geo-report-engineWrote 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/prashishh/seo-geo-report-engine/programmatic-seo)<a href="https://agentmods.dev/skills/prashishh/seo-geo-report-engine/programmatic-seo"><img src="https://agentmods.dev/badge/skills/prashishh/seo-geo-report-engine/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/prashishh/seo-geo-report-engine/programmatic-seo"><img src="https://agentmods.dev/badge/skills/prashishh/seo-geo-report-engine/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 | $0.00158 | $0.01573 |
| Opus 5 | $0.00079 | $0.00787 |
| Sonnet 5 | $0.00032 | $0.00315 |
| Haiku 4.5 | $0.00016 | $0.00157 |
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 9d 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
programmatic-seo
Plan + generate many pages from one template × a data set of rows without tripping
thin-content / doorway penalties. The IP is in playbooks/programmatic-seo.md (when it
works vs backfires, the "unique value per page" bar, the thin-content failure mode); this
skill is the operating procedure. Methodology: PERCEIVE → ANALYZE → VALIDATE → ACT,
falsifiable recommendations. Today is 2026-06-23; write absolute dates.
Inputs
projects/<client>/client.yml— domain, target keywords, competitors, locale.- Existing keyword / competitor research in
projects/<client>/research/. - Any first-party data the client can supply (pricing, coverage, catalog) in
inputs/.
Resolve context first: ./bin/mkt config show --project <client>.
Workflow
-
PERCEIVE — discover the keyword matrix (Ahrefs MCP, see
knowledge/ahrefs-mcp-map.md). From the seed term(s), find the real modifier pattern:keywords-explorer-matching-terms— all terms containing the seed (the dominant pattern).keywords-explorer-related-terms/keywords-explorer-search-suggestions— adjacent angles and the autocomplete tail; use to spot a second dimension.keywords-explorer-volume-by-country— localize per market before fixing the locale.
-
ANALYZE — define dimensions / modifiers. Pick enumerable dimensions whose cross-product has demand, e.g.
{service} × {city}. One strong dimension beats three weak ones. Build the candidate matrix as rows (one row = one page). -
VALIDATE — confirm real demand per combo and prune. Pull volume (and SERP type via
serp-overview) for each combination or a representative sample withkeywords-explorer-overview. Prune thin / no-demand combos and combos you have no data to differentiate. Record the volume threshold and kept-vs-pruned counts (a falsifiable assumption). -
VALIDATE — clear the "unique value per page" bar. Each row must carry data that does NOT appear on its siblings (real prices, computed averages, coverage, inventory, verified facts) — data, not swapped words. Diff two adjacent draft rows: if only the dimension values differ, it fails — find more data or cut the pattern. This is the QA gate; do not skip it.
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.
- 9d ago First seen · 111 lines · 158 tokens per session scan A 2fb0ac7dbf63
programmatic-seo is a skill published in the GitHub repository prashishh/seo-geo-report-engine (5 stars, last pushed 2mo ago), licensed MIT. It adds 158 tokens to every session and 1,573 once invoked, about $0.0008 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 2026-08-31.
Other skills, from other repositories
content-amplifier
Use when the user asks to "amplify influencer content with paid media", "set up whitelisting or Spark Ads", "decide which posts to boost", "repurpose influencer content", "turn one video into multiple ads", or "build a UGC asset library"; produces (paid mode) a content-selection scorecard, a paid amplification…
campaign-planner
Use when the user asks to "plan an influencer campaign", "build a campaign blueprint", "track or close a creator campaign", or "record a late campaign correction"; produces the plan and, when requested, a non-canonical evidence tracker with scoped identity, publication, reconciliation, close, and reopen receipts. Not…
inbox-placement-monitor
Use when the user asks to "track where my emails are actually landing after I send", "read my seed-list inbox vs spam vs promotions results", "trend my Gmail Postmaster / Microsoft SNDS reputation", or "did placement drop after my last send"; produces a per-provider inbox/spam/promotions placement read, a domain/IP…
subject-line-lab
Use when the user asks to "generate subject line variants", "pre-score my subject lines", or "will this subject get truncated / trigger spam filters"; produces a labeled subject + preheader variant set and a per-variant heuristic pre-score card — spam-trigger flags, length/truncation across desktop + mobile…
email-sequence-designer
Use when the user asks to "design a welcome flow", "set up an abandoned-cart sequence", "build a light re-engagement branch inside a lifecycle flow", or "plan a cold-outbound sequence"; produces general lifecycle automation flows (welcome, cart, browse-abandon, post-purchase, in-flow re-engagement, B2B cold outbound)…
newsletter-monetization-planner
Use when the user asks to "monetize my newsletter", "build a sponsorship rate card", or "model paid-subscription revenue"; produces a revenue model (paid tiers, ad/sponsorship inventory + CPM/flat rate card, referral/boost loops), a list-growth ↔ revenue projection, and honest-offer / disclosure checks for the SEND-D…