abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
@yogsoth-aiInstall SkillAutomation
Skill
/design-data-extraction
Define a structured extraction form, field semantics, coding rules, and missing-data handling for evidence synthesis.
Claude Code
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill design-data-extraction --agent claude-code
Codex
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill design-data-extraction -a codex -y
Cursor
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill design-data-extraction -a cursor -y
Gemini CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill design-data-extraction -a gemini-cli -y
GitHub Copilot
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill design-data-extraction -a github-copilot -y
OpenCode
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill design-data-extraction -a opencode -y
Windsurf
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill design-data-extraction -a windsurf -y
SKILL.md
design-data-extraction.SKILL.mdname: design-data-extraction
description: "Define a structured extraction form, field semantics, coding rules, and missing-data handling for evidence synthesis."
design-data-extraction
Purpose
Define a structured extraction form, field semantics, coding rules, and missing-data handling for evidence synthesis.
Input contract
required: [evidence_question, record_schema]
optional: [coding_guidance, unit_rules, quality_fields]
constraints: [field definitions and missing-data states must be explicit]
Procedure
1. Derive fields from the evidence question and synthesis outputs. 2. Define types, units, allowed values, coding rules, and provenance fields. 3. Specify unknown, not reported, not applicable, and ambiguous states. 4. Pilot the form on boundary records and revise only documented ambiguities.
If the extraction schema is fixed and studies are ready for methodological appraisal, consider `audit-study-validity` as the next tactic.
Output contract
produces: [extraction_schema, coding_rules, missing_data_policy, pilot_issues]
delta_fields: [decisions, assumption_updates, uncertainties, open_questions]
Quality gates
- Every output field has an extraction source and semantic definition.
- Missingness is not conflated with a negative finding.
Failure and counterexamples
Do not add fields that cannot affect the synthesis, and do not collapse incomparable units.
Provenance map
- `resolved: data-extraction-form`
Read more
name: design-data-extraction description: "Define a structured extraction form, field semantics, coding rules, and missing-data handling for evidence synthesis."
design-data-extraction
Purpose
Define a structured extraction form, field semantics, coding rules, and missing-data handling for evidence synthesis.
Input contract
required: [evidence_question, record_schema] optional: [coding_guidance, unit_rules, quality_fields] constraints: [field definitions and missing-data states must be explicit]
Procedure
1. Derive fields from the evidence question and synthesis outputs. 2. Define types, units, allowed values, coding rules, and provenance fields. 3. Specify unknown, not reported, not applicable, and ambiguous states. 4. Pilot the form on boundary records and revise only documented ambiguities.
If the extraction schema is fixed and studies are ready for methodological appraisal, consider `audit-study-validity` as the next tactic.
Output contract
produces: [extraction_schema, coding_rules, missing_data_policy, pilot_issues] delta_fields: [decisions, assumption_updates, uncertainties, open_questions]
Quality gates
- Every output field has an extraction source and semantic definition.
- Missingness is not conflated with a negative finding.
Failure and counterexamples
Do not add fields that cannot affect the synthesis, and do not collapse incomparable units.
Provenance map
- `resolved: data-extraction-form`
Ships withde-anthropocentric-research-engine
A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.
507200 skills
Stars on GitHub
Momentum
- stars in total
- 507
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Questions about design-data-extraction.
- Which coding agents can use design-data-extraction?
- design-data-extraction installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.