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Get Started Free →Tactic: Inductive/abductive path — describe anomalous phenomena, generate candidate explanations, rank by plausibility
.claude/skills/yogsoth-ai-anomaly-driven-abduction/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 330% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 29% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 27% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 41% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 81% | 0% |
Inductive/abductive path — precisely describe anomalous phenomena that existing theory cannot explain, generate multiple candidate explanations, rank by plausibility, and provide a structured basis for abductive hypotheses.
The starting point of abduction is "surprise" — an observed phenomenon inconsistent with existing theoretical predictions. This tactic forces CC to first precisely describe the anomaly (no vagueness allowed), then systematically generate explanations (not allowed to think of only one), and finally rank by plausibility (no subjective preference allowed).
None of the three steps can be omitted: imprecise description means explanations cannot be focused; insufficient explanations make ranking meaningless; ranking without basis turns hypothesis selection into guesswork.
| SOP | Responsibility | When to call | |-----|------|---------| | anomaly-characterization | Precisely describe the anomalous phenomenon: what was observed, deviation from expectation, conditions of occurrence, excluded trivial explanations | Required in all modes, execute first | | explanation-generation | Generate multiple candidate explanations (abductive hypotheses); each explanation must fully account for the anomaly | Required in all modes, after anomaly-characterization | | plausibility-ranking | Rank candidate explanations by plausibility criteria (prior probability, explanatory power, parsimony, testability) | Required in all modes, execute last |
Simplified (S tier, single anomaly)
Standard (M tier, 1-3 related anomalies)
Deep (L tier, complex anomaly cluster)
Report to the calling strategy after execution:
<!-- BEGIN available-tables (generated) -->
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use | | --- | --- | | anomaly-characterization | SOP: Describe and classify anomalous phenomena that existing theory cannot explain | | explanation-generation | SOP: generate a list of candidate explanations for an anomalous phenomenon | | plausibility-ranking | SOP: rank candidate explanations by plausibility using multi-dimensional weighted scoring |
<!-- END available-tables (generated) -->
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 6,524 | 21,658 | +232% | 1 | 1 | 0% | 1,020 | 4,384 | +330% | 0 | 0 | — |
case-02 | fail→pass | 15,336 | 13,444 | -12% | 1 | 1 | 0% | 2,283 | 2,953 | +29% | 0 | 0 | — |
case-03 | fail→pass | 17,239 | 15,149 | -12% | 1 | 1 | 0% | 2,554 | 3,240 | +27% | 0 | 0 | — |
case-04 | fail→fail | 18,785 | 25,564 | +36% | 1 | 1 | 0% | 2,886 | 5,152 | +79% | 0 | 0 | — |
case-05 | pass→pass | 14,150 | 29,681 | +110% | 1 | 1 | 0% | 2,318 | 6,093 | +163% | 0 | 0 | — |
case-06 | fail→pass | 24,473 | 30,581 | +25% | 1 | 1 | 0% | 3,907 | 5,507 | +41% | 0 | 0 | — |
case-07 | fail→pass | 18,921 | 26,513 | +40% | 1 | 1 | 0% | 2,857 | 5,170 | +81% | 0 | 0 | — |
case-08 | pass→pass | 17,154 | 20,352 | +19% | 1 | 1 | 0% | 2,590 | 3,881 | +50% | 0 | 0 | — |
case-09 | pass→pass | 10,907 | 15,216 | +40% | 1 | 1 | 0% | 1,718 | 3,334 | +94% | 0 | 0 | — |
case-10 | fail→pass | 11,108 | 17,242 | +55% | 1 | 1 | 0% | 1,660 | 3,347 | +102% | 0 | 0 | — |
case-11 | pass→pass | 19,223 | 23,379 | +22% | 1 | 1 | 0% | 3,016 | 4,561 | +51% | 0 | 0 | — |
case-12 | pass→pass | 26,627 | 25,438 | -4% | 1 | 1 | 0% | 4,284 | 4,807 | +12% | 0 | 0 | — |
case-13 | fail→pass | 17,971 | 24,869 | +38% | 1 | 1 | 0% | 2,844 | 4,959 | +74% | 0 | 0 | — |
case-14 | pass→pass | 20,645 | 28,518 | +38% | 1 | 1 | 0% | 3,185 | 5,248 | +65% | 0 | 0 | — |
case-15 | pass→pass | 8,650 | 8,854 | +2% | 1 | 1 | 0% | 1,784 | 2,389 | +34% | 0 | 0 | — |
case-16 | pass→fail | 7,733 | 10,777 | +39% | 1 | 1 | 0% | 1,525 | 2,773 | +82% | 0 | 0 | — |
case-17 | pass→fail | 12,084 | 24,654 | +104% | 1 | 1 | 0% | 2,543 | 5,555 | +118% | 0 | 0 | — |
case-18 | fail→pass | 15,557 | 15,798 | +2% | 1 | 1 | 0% | 2,511 | 3,368 | +34% | 0 | 0 | — |
case-19 | pass→pass | 18,041 | 31,154 | +73% | 1 | 1 | 0% | 2,754 | 6,055 | +120% | 0 | 0 | — |
case-20 | pass→pass | 16,377 | 21,466 | +31% | 1 | 1 | 0% | 2,442 | 4,196 | +72% | 0 | 0 | — |
case-21 | fail→fail | 25,229 | 30,996 | +23% | 1 | 1 | 0% | 4,090 | 6,096 | +49% | 0 | 0 | — |
case-22 | fail→fail | 12,597 | 12,449 | -1% | 1 | 1 | 0% | 1,978 | 2,667 | +35% | 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 +27 percentage points is the difference between those two pass rates over the 22 comparable cases. 2 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.