define-criteria

SkillDev tools

Lets your agent turn a research goal into clear, measurable criteria for comparing options.

Available today. Use it from your connected AI after setup.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the define-criteria skill

About this skill

Derive explicit evaluation criteria from the research objective and candidate set.

What this skill tells your AI

The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/define-criteria/SKILL.md and read by ahel’s review.

Purpose

Derive explicit evaluation criteria from the research objective and candidate set.

Input contract

required: [research_objective, candidate_set, decision_context]
optional: [stakeholder_priorities, measurement_constraints, candidate_domains]
constraints: [criteria must be mutually interpretable across candidates]

Procedure

  1. Extract desired outcomes and constraints from the objective.
  2. Translate them into candidate-discriminating criteria with definitions and units.
  3. Check completeness, overlap, direction, and measurability.
  4. Return the criterion schema and unresolved measurement questions.

Output contract

produces: [criterion_schema, measurement_definitions, direction_labels, coverage_notes]
delta_fields: [findings, open_questions, uncertainties]

Quality gates

  • Criteria count is between 3 and 12 unless caller explicitly authorizes another range.
  • Every criterion has name, definition, unit, and higher/lower-is-better direction.
  • Criteria are non-overlapping enough that double counting is documented.

Parameterization

Caller supplies objective schema, candidate schema, criterion count bounds, measurement units, direction vocabulary, and overlap policy.

Failure and counterexamples

Reject vague criteria lacking an observable measurement or criteria that cannot distinguish any candidate.

Provenance map

  • resolved: criterion-definition
  • concept: hypothesis-formation/scoring-matrix-construction (criteria-extraction core)
  • resolved: hypothesis-formation-scoring-matrix-construction
  • intermediate: Pass4/define-success-criteria

Preserved source criteria ledger

sourcecriterion
criterion-definitionCriteria count is between 3-12.
criterion-definitionEach criterion includes name, definition, unit of measurement, and direction (higher-is-better/lower-is-better).
convergence-scoring-matrix-constructionNormalization method matches the aggregation method.
convergence-scoring-matrix-constructionSensitivity testing perturbs at least 3 weight parameters by +/-10%.

Signals

GitHub stars
501
Forks
41
Last commit
Sep 2026
Advanced
Catalog kind
skill
Key
define-criteria
Source
github.com/yogsoth-ai/de-anthropocentric-research-engine