abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Generate a non-dominated frontier for a multi-objective candidate/portfolio problem.
Claude Code
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill optimize-pareto-frontier --agent claude-code
Codex
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill optimize-pareto-frontier -a codex -y
Cursor
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill optimize-pareto-frontier -a cursor -y
Gemini CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill optimize-pareto-frontier -a gemini-cli -y
GitHub Copilot
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill optimize-pareto-frontier -a github-copilot -y
OpenCode
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill optimize-pareto-frontier -a opencode -y
Windsurf
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill optimize-pareto-frontier -a windsurf -y
name: optimize-pareto-frontier description: "Generate a non-dominated frontier for a multi-objective candidate/portfolio problem."
Generate a non-dominated frontier for a multi-objective candidate or portfolio problem while preserving objective tradeoffs.
required: [candidate_set, objective_schema, constraint_schema, evaluation_records] optional: [dominance_rule, feasibility_policy, tie_policy] constraints: [objective directions, scales, feasibility rules, and missing-value handling are explicit]
1. Normalize candidate evaluations to the declared objective directions and units without erasing provenance. 2. Remove infeasible candidates according to hard constraints and mark unknown feasibility separately. 3. Compare every feasible candidate pair for dominance; retain candidates not dominated on all objectives. 4. Verify frontier membership, record sacrificed objectives, and emit unresolved comparisons.
produces: [pareto_frontier, dominance_matrix, excluded_candidates, unresolved_comparisons] delta_fields: [findings, evidence_updates, uncertainties, decisions, open_questions]
Do not collapse objectives into one score unless the objective schema explicitly authorizes it. Unknown values cannot establish dominance.
A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.
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