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Get Started Free →SOP wrapping vault_search — BM25 full-text search across vault pages. Returns ranked results with snippets.
.claude/skills/yogsoth-ai-wiki-search/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-07 | ✗→✓ | ▲ Improved | 292% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 66% | 0% |
| case-09 | ✗→✓ | ▲ Improved | -66% | 0% |
| case-10 | ✗→✓ | ▲ Improved | -50% | 0% |
| case-13 | ✗→✓ | ▲ Improved | 7% | 0% |
Search the vault for existing pages matching a query. Used before creating new pages (deduplication) and for finding related content.
<HARD-GATE> Query must be non-empty and contain at least one meaningful term. Do NOT search with single characters or pure stop words. </HARD-GATE>
vault_search
| Param | Required | Description | |-------|----------|-------------| | query | yes | Search query (natural language or keywords) | | type | no | Filter by entity types (e.g., "concept", "claim"]) | | tags | no | Filter by tags | | limit | no | Max results (default 20) |
vault_search with query and optional filtersReturns: { results_count: number, top_score: number, potential_duplicates: string[] }
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 6,556 | 8,834 | +35% | 1 | 1 | 0% | 1,103 | 456 | -59% | 0 | 0 | — |
case-02 | fail→fail | 23,774 | 9,812 | -59% | 1 | 1 | 0% | 1,970 | 446 | -77% | 0 | 0 | — |
case-18 | fail→fail | 13,320 | 9,599 | -28% | 1 | 1 | 0% | 506 | 406 | -20% | 0 | 0 | — |
case-03 | fail→fail | 26,198 | 10,282 | -61% | 1 | 1 | 0% | 4,005 | 525 | -87% | 0 | 0 | — |
case-04 | pass→pass | 45,243 | 48,090 | +6% | 1 | 1 | 0% | 7,637 | 7,019 | -8% | 0 | 0 | — |
case-05 | pass→fail | 9,959 | 14,645 | +47% | 1 | 1 | 0% | 779 | 650 | -17% | 0 | 0 | — |
case-06 | fail→fail | 14,920 | 16,114 | +8% | 1 | 1 | 0% | 202 | 504 | +150% | 0 | 0 | — |
case-07 | fail→pass | 2,788 | 10,033 | +260% | 1 | 1 | 0% | 230 | 901 | +292% | 0 | 0 | — |
case-08 | fail→pass | 9,822 | 5,494 | -44% | 1 | 1 | 0% | 704 | 1,167 | +66% | 0 | 0 | — |
case-09 | fail→pass | 11,923 | 7,575 | -36% | 1 | 1 | 0% | 1,951 | 665 | -66% | 0 | 0 | — |
case-10 | fail→pass | 10,894 | 7,181 | -34% | 1 | 1 | 0% | 1,006 | 505 | -50% | 0 | 0 | — |
case-11 | fail→fail | 13,421 | 10,294 | -23% | 1 | 1 | 0% | 1,381 | 394 | -71% | 0 | 0 | — |
case-12 | fail→fail | 17,464 | 15,024 | -14% | 1 | 1 | 0% | 574 | 450 | -22% | 0 | 0 | — |
case-13 | fail→pass | 8,698 | 2,510 | -71% | 1 | 1 | 0% | 557 | 598 | +7% | 0 | 0 | — |
case-14 | fail→fail | 12,891 | 14,362 | +11% | 1 | 1 | 0% | 1,328 | 497 | -63% | 0 | 0 | — |
case-15 | fail→fail | 16,390 | 13,836 | -16% | 1 | 1 | 0% | 300 | 465 | +55% | 0 | 0 | — |
case-16 | fail→fail | 12,236 | 13,663 | +12% | 1 | 1 | 0% | 1,364 | 418 | -69% | 0 | 0 | — |
case-17 | fail→fail | 9,232 | 12,665 | +37% | 1 | 1 | 0% | 765 | 741 | -3% | 0 | 0 | — |
case-19 | pass→pass | 20,565 | 8,366 | -59% | 1 | 1 | 0% | 2,122 | 882 | -58% | 0 | 0 | — |
case-20 | fail→fail | 12,373 | 10,365 | -16% | 1 | 1 | 0% | 1,067 | 597 | -44% | 0 | 0 | — |
case-21 | fail→pass | 18,610 | 9,928 | -47% | 1 | 1 | 0% | 2,198 | 1,096 | -50% | 0 | 0 | — |
case-22 | fail→pass | 7,988 | 8,077 | +1% | 1 | 1 | 0% | 1,450 | 785 | -46% | 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, and 10 counted toward the lift figure. The other 12 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +27 percentage points is the difference between those two pass rates over the 10 comparable cases. 4 cases got worse with the skill loaded, and they are included in that figure.
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.