yogsoth-ai/de-anthropocentric-research-engine

define-analysis-dimensions

Identify approximately independent dimensions/axes that span the relevant problem, design, or validity space and define their semantics.

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How to use

  1. Copy the installation command and review the source package before installing it in your own agent environment.
  2. Check the source document for required tools, credentials and supported hosts.
  3. Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill define-analysis-dimensions

Before you start

  • Installation does not include a model subscription, API allowance or permission to access your files.
  • Repository stars and installation counts describe activity, not an independent quality or security test.
Original skill document

Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.

define-analysis-dimensions

Purpose

Define approximately independent, measurable axes that span a problem, design, or validity space.

Input contract

yaml
required: [problem_or_artifact, target_outcome, dimension_ontology]
optional: [candidate_axes, domain_constraints, measurement_plan]
constraints: [each axis has semantics, type, direction, and measurement rule; correlated axes are flagged]

Procedure

  1. Extract factors and conditions relevant to the target outcome.
  2. Group candidates into dimensions and test approximate independence.
  3. Define each dimension's domain, units, direction, and observability.
  4. Return the dimension set with exclusions and unresolved dependencies.

If each analysis dimension has a clear meaning and admissible type, consider enumerate-dimension-values as the next tactic.

Output contract

yaml
produces: [dimension_set, axis_definitions, independence_notes, coverage_scope]
delta_fields: [findings, evidence_updates, uncertainties, open_questions]

Quality gates

  • Every retained axis is independent enough for the caller's analysis and is measurable under the supplied plan.
  • Parameter-space mapping covers all dimensions relevant to assertion validity; omitted axes require a reason.
  • Do not confuse a value/level with the dimension that contains it.

Parameterization

The caller must provide the target problem, outcome, axis ontology, candidate factors, domain bounds, measurement units, and independence criterion.

Failure and counterexamples

Reject duplicate axes, dimensions with no observable values, or an independence claim unsupported by a comparison.

Provenance map

  • resolved: deep-insight/variation-axis-definition
  • resolved: stress-test/parameter-space-mapping
  • resolved: creative-ideation/parameter-identification
  • intermediate: Pass3/map-parameter-space
  • intermediate: Pass3/identify-dimensions

Preserved source criteria ledger

sourcephysical linekindsource criterion
deep-insight/variation-axis-definition14structuralIdentify orthogonal axes, ensuring they are independent, measurable, and span the parameter space.

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