abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Assess whether a benchmark measures its claimed capability using content, convergent, discriminant, and confound analysis.
Claude Code
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill assess-construct-validity --agent claude-code
Codex
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill assess-construct-validity -a codex -y
Cursor
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill assess-construct-validity -a cursor -y
Gemini CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill assess-construct-validity -a gemini-cli -y
GitHub Copilot
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill assess-construct-validity -a github-copilot -y
OpenCode
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill assess-construct-validity -a opencode -y
Windsurf
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill assess-construct-validity -a windsurf -y
name: assess-construct-validity description: "Assess whether a benchmark measures its claimed capability using content, convergent, discriminant, and confound analysis."
Assess whether a benchmark or evaluation construct measures the claimed capability rather than content cues, confounds, or unrelated skill.
required: [construct_claim, benchmark_specification, evaluation_records] optional: [content_analysis, convergent_measures, discriminant_measures, confound_hypotheses] constraints: [each validity judgment requires an observable indicator, comparison basis, and provenance]
1. State the target construct and map benchmark tasks, labels, and metrics to its intended components. 2. Check content coverage and plausible construct-irrelevant cues against the benchmark specification. 3. Compare convergent and discriminant evidence where available, preserving missing comparisons. 4. Test confound hypotheses with controlled contrasts or artifact probes and record residual uncertainty.
If construct validity depends on whether the operationalization covers the intended domain, consider `map-coverage-space` as the next tactic.
produces: [construct_map, content_validity_assessment, convergent_discriminant_evidence, confound_report, validity_judgment] delta_fields: [findings, evidence_updates, uncertainties, decisions, open_questions]
Do not infer construct validity from a high score, face validity, or agreement with another measure that shares the same confound.
A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.
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