Como usar
- Copie o comando e verifique o pacote antes de instalar no seu ambiente de agente.
- Consulte no original as ferramentas, credenciais e ambientes necessários.
- Descreva os dados de entrada e a entrega esperada; confira a saída com as fontes.
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill define-analysis-dimensionsAntes de começar
- A instalação não inclui assinatura de modelo, franquia API ou acesso aos seus arquivos.
- Estrelas e instalações indicam atividade, não um teste independente de qualidade ou segurança.
Documento original do Skill
Renderizado do repositório de origem, preservando títulos, exemplos, código, tabelas, links e imagens.
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
- Extract factors and conditions relevant to the target outcome.
- Group candidates into dimensions and test approximate independence.
- Define each dimension's domain, units, direction, and observability.
- 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
| source | physical line | kind | source criterion |
|---|---|---|---|
| deep-insight/variation-axis-definition | 14 | structural | Identify orthogonal axes, ensuring they are independent, measurable, and span the parameter space. |
