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Strategy for continuous rating updates using Elo, Glicko-2, TrueSkill 2, and Whole-History Rating for live ranking systems and A/B testing.
Passed 21 of 21 test cases with the skill, and 11 of 21 without it.
and 15 more in the full report
11 fixed11 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
Which Standard Operating Procedure (SOP) is responsible for producing the public ranking summary artifact once ratings have stabilized and consistency audits are complete?
| Checked | Without skill | With skill |
|---|---|---|
| The SOP specified for artifact generation is ranking-synthesis. | Missed | Passed |
The instructions your model reads when the skill loads.
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 |
candidates: {} # 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}
test cases passed, vs 11 / 21 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.