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Automation
Skill

/detect-breakpoint

Locate the point or region where performance/validity changes regime or the claim flips.

From plugin
de-anthropocentric-research-engine
499200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill detect-breakpoint --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/detect-breakpoint

Context preview

The summary Claude sees to decide when to auto-load this skill.

Locate the point or region where performance/validity changes regime or the claim flips.

SKILL.md

detect-breakpoint.SKILL.md
name: detect-breakpoint
description: "Locate the point or region where performance/validity changes regime or the claim flips."

detect-breakpoint

Purpose

Locate the point or region where performance, validity, or a claim changes regime.

Input contract

required: [ordered_observations, target_metric, flip_or_regime_rule]
optional: [candidate_axis, smoothing_rule, uncertainty_bounds]
constraints: [ordering and metric direction are explicit]

Procedure

1. Sort observations along the declared axis and validate comparability. 2. Detect abrupt flips, slope changes, saturation, or regime transitions. 3. Estimate boundary region and attach uncertainty. 4. Return witness observations and follow-up tests.

Output contract

produces: [breakpoint_region, regime_label, witness_observations, uncertainty, follow_up_tests]
delta_fields: [findings, uncertainties, open_questions]

Quality gates

  • A breakpoint requires observations on both sides or an explicit one-sided limitation.
  • Metric direction and flip rule are declared before detection.
  • Smoothing or interpolation never replaces raw witnesses.

Parameterization

Caller supplies observation schema, axis ordering, metric, flip/regime rule, smoothing, and uncertainty policy.

Failure and counterexamples

Reject boundaries inferred from unvalidated ordering, single noisy points, or hidden smoothing.

Provenance map

  • concept: stress-test/breakpoint-detection
  • concept: deep-insight/controlled-perturbation
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Ships withde-anthropocentric-research-engine

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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