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Automation
Skill

/estimate-performance-headroom

Estimate practical/human/theoretical ceilings and remaining performance headroom under stated assumptions.

From plugin
de-anthropocentric-research-engine
499200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill estimate-performance-headroom --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/estimate-performance-headroom

Context 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.

SKILL.md

estimate-performance-headroom.SKILL.md
name: estimate-performance-headroom
description: "Estimate practical/human/theoretical ceilings and remaining performance headroom under stated assumptions."

estimate-performance-headroom

Purpose

Estimate practical, human, or theoretical ceilings and remaining performance headroom under stated assumptions.

Input contract

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]

Procedure

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.

Output contract

produces: [ceiling_estimates, headroom_estimates, assumption_register, uncertainty_priorities]
delta_fields: [findings, evidence_updates, uncertainties, recommended_jumps]

Quality gates

  • Ceiling and current score are comparable.
  • Headroom is not reported as an absolute fact when assumptions dominate.

Failure and counterexamples

Do not use an upper-bound theorem as a practical ceiling or equate benchmark maximum with human or task optimum.

Provenance map

  • `resolved: headroom-estimation`
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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.

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Python
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Apache-2.0
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Repo: yogsoth-ai/de-anthropocentric-research-engine