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Get Started Free →Programmatic page generation at scale using template-based SEO and data pipelines: keyword pattern mining, template architecture, and indexation for 100-100K+ pages. Use when building SEO pages at scale or scoping a programmatic SEO build.
.claude/skills/borghei-programmatic-seo/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | 161% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 264% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 86% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 39% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 50% | 0% |
Production-grade framework for building SEO page sets at scale. Covers the full lifecycle from keyword pattern discovery through template design, data pipeline construction, quality assurance, and post-launch optimization. Designed for deployments ranging from 50 to 100,000+ pages.
[variable] structures, map head/torso/long-tail/zero-volume distribution, and classify search intent.Use this skill when:
Do NOT use when:
Before scoping the build, confirm these inputs. If any is unknown or vague, ASK — do not assume:
[variable] structure with 50+ variations (drives keyword mining and template variables)Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
bash# Analyze keyword patterns for pSEO opportunities python scripts/keyword_pattern_miner.py --keywords keywords.csv --json # Score page templates for content quality and uniqueness python scripts/template_scorer.py --template template.html --data sample_data.json # Validate data quality for pSEO data pipeline python scripts/data_validator.py --file data.csv --rules rules.json --json
Load the reference that matches the phase you are in — keep this file lean and pull detail on demand:
In scope:
Out of scope:
Known limitations:
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-04 | fail→pass | 15,272 | 26,057 | +71% | 1 | 1 | 0% | 2,346 | 6,124 | +161% | 0 | 0 | — |
case-05 | fail→pass | 6,556 | 11,181 | +71% | 1 | 1 | 0% | 911 | 3,313 | +264% | 0 | 0 | — |
case-01 | fail→fail | 27,239 | 21,865 | -20% | 1 | 1 | 0% | 4,151 | 4,888 | +18% | 0 | 0 | — |
case-02 | fail→fail | 33,777 | 29,690 | -12% | 1 | 1 | 0% | 5,255 | 6,108 | +16% | 0 | 0 | — |
case-03 | fail→fail | 21,602 | 26,744 | +24% | 1 | 1 | 0% | 3,325 | 5,776 | +74% | 0 | 0 | — |
case-06 | pass→pass | 11,674 | 13,527 | +16% | 1 | 1 | 0% | 1,606 | 3,560 | +122% | 0 | 0 | — |
case-07 | fail→pass | 6,500 | 2,487 | -62% | 1 | 1 | 0% | 991 | 1,839 | +86% | 0 | 0 | — |
case-08 | fail→pass | 8,702 | 3,563 | -59% | 1 | 1 | 0% | 1,417 | 1,966 | +39% | 0 | 0 | — |
case-09 | fail→pass | 7,847 | 2,715 | -65% | 1 | 1 | 0% | 1,240 | 1,855 | +50% | 0 | 0 | — |
case-10 | fail→pass | 18,265 | 16,334 | -11% | 1 | 1 | 0% | 2,431 | 3,803 | +56% | 0 | 0 | — |
case-11 | fail→pass | 10,492 | 7,330 | -30% | 1 | 1 | 0% | 1,526 | 2,550 | +67% | 0 | 0 | — |
case-12 | fail→fail | 42,189 | 39,407 | -7% | 1 | 1 | 0% | 6,180 | 7,616 | +23% | 0 | 0 | — |
case-13 | fail→fail | 8,873 | 17,634 | +99% | 1 | 1 | 0% | 1,428 | 4,468 | +213% | 0 | 0 | — |
case-14 | fail→fail | 16,038 | 18,421 | +15% | 1 | 1 | 0% | 2,977 | 4,809 | +62% | 0 | 0 | — |
case-15 | fail→fail | 18,092 | 21,547 | +19% | 1 | 1 | 0% | 3,310 | 5,280 | +60% | 0 | 0 | — |
case-16 | fail→fail | 20,805 | 29,538 | +42% | 1 | 1 | 0% | 3,097 | 5,893 | +90% | 0 | 0 | — |
case-17 | pass→pass | 12,386 | 17,799 | +44% | 1 | 1 | 0% | 2,177 | 3,926 | +80% | 0 | 0 | — |
case-18 | pass→pass | 20,638 | 17,861 | -13% | 1 | 1 | 0% | 2,956 | 4,109 | +39% | 0 | 0 | — |
case-19 | fail→pass | 12,102 | 6,902 | -43% | 1 | 1 | 0% | 1,724 | 2,547 | +48% | 0 | 0 | — |
case-20 | fail→pass | 12,544 | 5,548 | -56% | 1 | 1 | 0% | 1,920 | 2,377 | +24% | 0 | 0 | — |
case-21 | fail→pass | 10,797 | 5,737 | -47% | 1 | 1 | 0% | 1,776 | 2,285 | +29% | 0 | 0 | — |
case-22 | fail→pass | 7,900 | 2,875 | -64% | 1 | 1 | 0% | 1,044 | 1,843 | +77% | 0 | 0 | — |
case-23 | pass→pass | 12,568 | 22,781 | +81% | 1 | 1 | 0% | 1,998 | 5,332 | +167% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +48 percentage points is the difference between those two pass rates over the 23 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.