abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Estimate practical/human/theoretical ceilings and remaining performance headroom under stated assumptions.
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill estimate-performance-headroom --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/estimate-performance-headroomContext preview
The summary Claude sees to decide when to auto-load this skill.
Estimate practical/human/theoretical ceilings and remaining performance headroom under stated assumptions.
name: estimate-performance-headroom description: "Estimate practical/human/theoretical ceilings and remaining performance headroom under stated assumptions."
Estimate practical, human, or theoretical ceilings and remaining performance headroom under stated assumptions.
required: [current_performance, ceiling_reference, metric_schema] optional: [human_baseline, oracle_bound, task_constraints, uncertainty_model] constraints: [each ceiling must name its population, conditions, and assumptions]
1. Define the relevant ceiling and align its metric and conditions with current performance. 2. Estimate the gap and uncertainty to each applicable ceiling. 3. Separate attainable, theoretical, and assumption-dependent headroom. 4. Identify evidence needed to reduce the dominant uncertainty.
produces: [ceiling_estimates, headroom_estimates, assumption_register, uncertainty_priorities] delta_fields: [findings, evidence_updates, uncertainties, recommended_jumps]
Do not use an upper-bound theorem as a practical ceiling or equate benchmark maximum with human or task optimum.
The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.
Repo: yogsoth-ai/de-anthropocentric-research-engine
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