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Get Started Free →Strategy for continuous rating updates using Elo, Glicko-2, TrueSkill 2, and Whole-History Rating for live ranking systems and A/B testing.
.claude/skills/yogsoth-ai-dynamic-tracking/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -10% | 0% |
| case-02 | ✗→✓ | ▲ Improved | -14% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 30% | 0% |
| case-04 | ✗→✓ | ▲ Improved | -46% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -21% | 0% |
Maintain live rankings that update incrementally as new comparisons arrive. Suitable for ongoing evaluation, A/B testing, and systems where candidates enter/exit over time. Tracks rating uncertainty and temporal dynamics.
| Resource | Allocation | |----------|-----------| | Comparisons per update | 1+ (online update) | | Rating recalculation | After each comparison or micro-batch | | Stability window | Last 20-50 comparisons for convergence check | | Decay handling | Increase uncertainty for inactive candidates |
yamlcandidates: {} # id → {mu, sigma, last_active, history: []} comparison_log: [] # [{pair, winner, timestamp, context}] method: "" # elo | glicko2 | trueskill2 | whr parameters: {} # K-factor, tau, beta, etc. iteration: 0 window_size: 30 convergence: {stable: false, score: 0.0}
a. Run comparison-executor (or accept external result) b. Run rating-update with online method c. Every window_size comparisons, run convergence-check
yamlcurrent_ranking: - {rank: 1, candidate: "...", mu: 1842, sigma: 45, games: 23} - {rank: 2, candidate: "...", mu: 1798, sigma: 52, games: 18} method: glicko2 total_comparisons: 342 last_updated: "2026-05-19T14:30:00Z" rating_period: 7 top_movers: - {candidate: "...", delta: +120, last_5: "WWWLW"} stability_score: 0.88
<!-- BEGIN available-tables (generated) -->
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use | | --- | --- | | adaptive-pair-selection | Iteratively select maximally informative pairs, execute comparisons, update ratings, and check convergence until ranking stabilizes. | | consistency-audit-loop | Detect preference cycles, localize inconsistent judgments, request corrections, and recompute ratings until consistency threshold is met. |
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use | | --- | --- | | ranking-synthesis | Produce the final ranking artifact from converged ratings and consistency report. |
<!-- 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-06 | pass→pass | 13,859 | 4,744 | -66% | 1 | 1 | 0% | 2,188 | 1,548 | -29% | 0 | 0 | — |
case-01 | fail→pass | 12,155 | 6,920 | -43% | 1 | 1 | 0% | 2,629 | 2,364 | -10% | 0 | 0 | — |
case-02 | fail→pass | 11,692 | 6,864 | -41% | 1 | 1 | 0% | 2,554 | 2,187 | -14% | 0 | 0 | — |
case-03 | fail→pass | 9,597 | 9,213 | -4% | 1 | 1 | 0% | 1,981 | 2,567 | +30% | 0 | 0 | — |
case-04 | fail→pass | 23,577 | 8,317 | -65% | 1 | 1 | 0% | 4,589 | 2,494 | -46% | 0 | 0 | — |
case-05 | pass→pass | 13,591 | 7,823 | -42% | 1 | 1 | 0% | 2,154 | 2,155 | +0% | 0 | 0 | — |
case-07 | fail→pass | 25,504 | 4,755 | -81% | 1 | 1 | 0% | 2,034 | 1,612 | -21% | 0 | 0 | — |
case-08 | pass→pass | 10,288 | 2,325 | -77% | 1 | 1 | 0% | 1,702 | 1,130 | -34% | 0 | 0 | — |
case-09 | pass→pass | 10,404 | 4,679 | -55% | 1 | 1 | 0% | 1,551 | 1,542 | -1% | 0 | 0 | — |
case-10 | pass→pass | 17,044 | 11,957 | -30% | 1 | 1 | 0% | 2,557 | 2,583 | +1% | 0 | 0 | — |
case-11 | fail→pass | 7,872 | 1,514 | -81% | 1 | 1 | 0% | 1,156 | 994 | -14% | 0 | 0 | — |
case-12 | fail→pass | 6,458 | 1,803 | -72% | 1 | 1 | 0% | 948 | 1,042 | +10% | 0 | 0 | — |
case-13 | fail→pass | 21,835 | 2,165 | -90% | 1 | 1 | 0% | 1,298 | 1,120 | -14% | 0 | 0 | — |
case-14 | fail→pass | 10,684 | 7,093 | -34% | 1 | 1 | 0% | 1,967 | 1,737 | -12% | 0 | 0 | — |
case-15 | pass→pass | 10,505 | 2,486 | -76% | 1 | 1 | 0% | 1,717 | 1,249 | -27% | 0 | 0 | — |
case-16 | pass→pass | 8,975 | 2,080 | -77% | 1 | 1 | 0% | 1,294 | 1,060 | -18% | 0 | 0 | — |
case-17 | fail→pass | 16,509 | 7,421 | -55% | 1 | 1 | 0% | 2,572 | 2,007 | -22% | 0 | 0 | — |
case-18 | fail→pass | 13,381 | 1,933 | -86% | 1 | 1 | 0% | 2,078 | 1,109 | -47% | 0 | 0 | — |
case-19 | pass→pass | 18,325 | 16,112 | -12% | 1 | 1 | 0% | 2,746 | 3,242 | +18% | 0 | 0 | — |
case-20 | pass→pass | 21,273 | 17,899 | -16% | 1 | 1 | 0% | 4,355 | 4,407 | +1% | 0 | 0 | — |
case-21 | pass→pass | 19,259 | 16,215 | -16% | 1 | 1 | 0% | 3,403 | 3,786 | +11% | 0 | 0 | — |
case-22 | pass→pass | 29,762 | 29,895 | +0% | 1 | 1 | 0% | 5,961 | 6,949 | +17% | 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 21 counted toward the lift figure. The other 1 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 +50 percentage points is the difference between those two pass rates over the 21 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.