Mode d’emploi
- Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
- Consultez le document original pour les outils, identifiants et environnements requis.
- Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill detect-breakpointAvant de commencer
- L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
- Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Document Skill original
Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.
detect-breakpoint
Purpose
Locate the point or region where performance, validity, or a claim changes regime.
Input contract
yaml
required: [ordered_observations, target_metric, flip_or_regime_rule]
optional: [candidate_axis, smoothing_rule, uncertainty_bounds]
constraints: [ordering and metric direction are explicit]Procedure
- Sort observations along the declared axis and validate comparability.
- Detect abrupt flips, slope changes, saturation, or regime transitions.
- Estimate boundary region and attach uncertainty.
- Return witness observations and follow-up tests.
Output contract
yaml
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
