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Get Started Free →Transform podcast transcripts into comprehensive content marketing suites including blog posts, social media content, newsletters, SEO-optimized articles, and timestamps. Use when user provides podcast transcripts or wants to repurpose podcast content.
.claude/skills/onewave-ai-podcast-to-content-suite/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-09 | ✗→✓ | ▲ Improved | 86% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 160% | 0% |
| case-14 | ✗→✓ | ▲ Improved | 48% | 0% |
| case-03 | ✓→✓ | ＝ Same ✓ | 10% | 0% |
| case-04 | ✓→✓ | ＝ Same ✓ | -15% | 0% |
Convert a podcast episode into a complete content marketing ecosystem: blog post, social posts, newsletter, show notes, audiograms, and SEO elements.
references/component-specs.md — per-asset requirements, best practices, and examplesreferences/output-template.md — full assembled output format with placeholdersActivate when the user provides a podcast transcript, asks to repurpose a podcast, wants content from audio, mentions podcast marketing or distribution, or needs blog posts, social content, or show notes from an episode.
references/component-specs.md section 1.references/output-template.md.Follow the best practices and example responses in references/component-specs.md to scope each request correctly.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 42,093 | 64,466 | +53% | 1 | 1 | 0% | 6,225 | 6,630 | +7% | 0 | 0 | — |
case-02 | fail→fail | 39,494 | 39,277 | -1% | 1 | 1 | 0% | 6,208 | 6,613 | +7% | 0 | 0 | — |
case-03 | pass→pass | 15,339 | 14,660 | -4% | 1 | 1 | 0% | 2,720 | 2,989 | +10% | 0 | 0 | — |
case-04 | pass→pass | 17,056 | 12,653 | -26% | 1 | 1 | 0% | 3,019 | 2,568 | -15% | 0 | 0 | — |
case-05 | pass→pass | 14,693 | 13,457 | -8% | 1 | 1 | 0% | 2,528 | 2,690 | +6% | 0 | 0 | — |
case-06 | fail→fail | 11,766 | 8,287 | -30% | 1 | 1 | 0% | 2,077 | 1,881 | -9% | 0 | 0 | — |
case-07 | fail→fail | 5,637 | 5,395 | -4% | 1 | 1 | 0% | 960 | 1,361 | +42% | 0 | 0 | — |
case-08 | fail→fail | 3,619 | 13,051 | +261% | 1 | 1 | 0% | 564 | 2,610 | +363% | 0 | 0 | — |
case-09 | fail→pass | 5,670 | 7,316 | +29% | 1 | 1 | 0% | 846 | 1,572 | +86% | 0 | 0 | — |
case-10 | fail→pass | 5,011 | 9,438 | +88% | 1 | 1 | 0% | 754 | 1,959 | +160% | 0 | 0 | — |
case-11 | fail→fail | 2,225 | 5,052 | +127% | 1 | 1 | 0% | 361 | 1,137 | +215% | 0 | 0 | — |
case-12 | fail→fail | 1,386 | 3,242 | +134% | 1 | 1 | 0% | 211 | 925 | +338% | 0 | 0 | — |
case-13 | fail→fail | 6,670 | 33,670 | +405% | 1 | 1 | 0% | 1,023 | 6,569 | +542% | 0 | 0 | — |
case-14 | fail→pass | 10,551 | 13,566 | +29% | 1 | 1 | 0% | 1,850 | 2,745 | +48% | 0 | 0 | — |
case-15 | fail→fail | 10,057 | 10,564 | +5% | 1 | 1 | 0% | 1,416 | 1,830 | +29% | 0 | 0 | — |
case-16 | fail→fail | 21,181 | 15,824 | -25% | 1 | 1 | 0% | 2,940 | 2,450 | -17% | 0 | 0 | — |
case-17 | fail→fail | 9,643 | 11,855 | +23% | 1 | 1 | 0% | 1,472 | 2,308 | +57% | 0 | 0 | — |
case-18 | pass→pass | 10,968 | 15,311 | +40% | 1 | 1 | 0% | 1,848 | 2,921 | +58% | 0 | 0 | — |
case-19 | pass→pass | 14,112 | 13,000 | -8% | 1 | 1 | 0% | 2,813 | 3,088 | +10% | 0 | 0 | — |
case-20 | fail→fail | 7,910 | 7,945 | +0% | 1 | 1 | 0% | 1,370 | 1,849 | +35% | 0 | 0 | — |
case-21 | pass→pass | 16,680 | 21,263 | +27% | 1 | 1 | 0% | 2,466 | 3,831 | +55% | 0 | 0 | — |
case-22 | fail→fail | 4,220 | 39,986 | +848% | 1 | 1 | 0% | 683 | 6,571 | +862% | 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. 22 cases were attempted. The headline lift of +14 percentage points is the difference between those two pass rates over the 22 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.