evolve-solution-population
SkillDev toolsLets your agent improve solutions by evolving a pool of candidates, keeping diverse options instead of settling on one early.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the evolve-solution-population skill
About this skill
Maintain a diverse population of candidate solutions, mutate/recombine variants, select under explicit fitness and novelty criteria, and iterate while preserving useful niches rather than collapsing prematurely to one winner.
What this skill tells your AI
The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/evolve-solution-population/SKILL.md and read by ahel’s review.
Purpose
Maintain diverse candidate solutions, mutate/recombine them, select under fitness and novelty criteria, and avoid premature convergence.
Input contract
mode_contracts:
mutation-selection: &evolution_input
required: [initial_solution_population, fitness_criteria]
optional: [mutation_operators, novelty_criteria, iteration_budget]
constraints: [population_members_must_be_comparable_under_declared_criteria]
novelty-preserving-evolution: *evolution_input
Execution protocol
Do not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.
- You MUST load skill
mutate-solution-populationto mutate or recombine the population. - You MUST load skill
select-solution-variantsto select solution variants. - You MUST load skill
measure-portfolio-diversityto measure portfolio diversity. - You MUST load skill
assess-sensitivityto assess selection sensitivity. - You MUST load skill
synthesize-ideato synthesize the retained set. If the retained variants require an explicit final ordering, considerrank-candidatesas the next tactic. Deviation: stop when added variation no longer changes the frontier or diversity objective; retain niche candidates when explicitly protected.
Mode branches
mutation-selection: mutate/recombine, score, and select across iterations.novelty-preserving-evolution: apply diversity pressure and protect useful niches before convergence.
Output contract
mode_contracts:
mutation-selection:
produces: [mechanism_to_design_mapping, generated_solutions, synthesis]
delta_fields: [findings, hypothesis_updates, uncertainties, decisions, open_questions]
novelty-preserving-evolution:
produces: [novelty_assessment]
delta_fields: [findings, hypothesis_updates, uncertainties, decisions, open_questions]
Thresholds and quality gates
- B: mutation/recombination lineage is traceable; selection criteria are explicit; diversity is measured before convergence.
Failure and counterexamples
Reject a single-winner result when novelty or niche preservation was required, and reject variants with untracked mutations.
Provenance map
creative-ideation/systematic-enumeration,evolution-strategy,variation-selection: resolved/concept according to exact v3 lookup.- Status:
creative-ideation/systematic-enumeration,evolution-strategyresolved;variation-selectionconcept.
Preserved source criteria ledger
- Preserve mutation, recombination, selection, diversity pressure, and niche preservation.
Context checkpoint / Delta notes
Append population lineage, fitness changes, diversity deltas, and retained niches.
Signals
- GitHub stars
- 501
- Forks
- 41
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Key
evolve-solution-population- Source
- github.com/yogsoth-ai/de-anthropocentric-research-engine