From thinking-frameworks-skills
Measures and protects diversity in a fantasy sports evolution engine by computing collapse metrics and injecting under-represented genotypes to prevent premature convergence.
How this skill is triggered — by the user, by Claude, or both
Slash command
/thinking-frameworks-skills:wc-population-diversityThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Implements the diversity-maintenance and selection-pressure ideas the Evolution document is explicit about: "plant breeders care about preserving genetic diversity; agent researchers care about maintaining behavioural diversity — same problem," and "selection pressure too high → population collapses; too low → progress is slow," and "repeatedly refining the same strategy leads to local optima" ...
Implements the diversity-maintenance and selection-pressure ideas the Evolution document is explicit about: "plant breeders care about preserving genetic diversity; agent researchers care about maintaining behavioural diversity — same problem," and "selection pressure too high → population collapses; too low → progress is slow," and "repeatedly refining the same strategy leads to local optima" (inbreeding). In this system, diversity isn't an aesthetic — it's what guarantees the manager sees a genuine choice (a cover path and a climb path), not six shades of the same template.
variance_band.- [ ] 1. Measure collapse metrics across the offspring set
- [ ] 2. Compare against diversity floors
- [ ] 3. If collapsed: inject an under-represented genotype and/or raise mutation; signal re-run of crossover+mutation
- [ ] 4. Tune selection pressure (widen/tighten the elite set)
- [ ] 5. Emit the diversity report
A healthy offspring set, before it reaches the manager, must satisfy:
These exist so decision-board-format.md's "2–4 genuinely distinct options spanning the variance spectrum" is structurally guaranteed, not hoped for.
The Evolution document's remedies plus the systems-thinking digest's broad-band respawn (system-dynamics.md §1–2):
invariants.md §4, §10). This guard is itself invariant: no learning-loop update may weaken it, and no archetype is ever zeroed. Before accepting any soft-prior tilt the scoreboard proposes, confirm it would not (a) drive a genotype's weight to zero, (b) let one genotype's blocks dominate every offspring, or (c) disable/soften this diversity check. If it would, reject the tilt and report it — the population search has started eating its own safety rail (the digest's #1 failure: premature convergence + the self-update overwriting the diversity monitor).system-dynamics.md §5). Population size N (the archetype count) is not monotonic. If the same decision rerun keeps producing qualitatively different winners — high run-to-run instability in which option leads — that's the signature of sitting near a critical N. Flag it to the Director to probe N−1 and N+1 rather than reflexively adding lanes; prefer the count that yields a stable, spectrum-spanning board. More archetypes is not automatically better.protect legitimately tilts the recommended default toward low-variance, but it must not delete the high-variance option from the board (re-weight, don't collapse — fitness-function.md).diversity_report:
mean_squad_overlap: <%>
distinct_captains: <n>
variance_bands_present: [low, medium, high?]
ownership_spread: cover↔differential coverage: ok|gap
collapsed: false|true
actions_taken: [ "injected A2 differential pod into offspring_3", "raised mutation 0.1→0.25", "re-ran crossover ×1" ]
board_flag: none | "low-diversity: options genuinely close this round"
This report goes to the Director so the manager knows whether the board is a wide-open choice or a narrow one. Transparency about diversity is part of the advisory contract.
npx claudepluginhub lyndonkl/claude --plugin thinking-frameworks-skillsApplies small, bounded perturbations to a recombined fantasy squad/plan to explore local variations while preserving feasibility. Use in the mutate stage after recombination, or when diversity requires more exploration.
Applies variation-selection-retention analysis to any evolving system — populations, strategies, cultures, products — to understand what survives and why.
Guides coaches through systematic observation, diagnosis, and decision-making for tactical, personnel, or strategic adjustments during competition halftimes or stoppages.