How to use
- Copy the installation command and review the source package before installing it in your own agent environment.
- Check the source document for required tools, credentials and supported hosts.
- 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 normalize-gapBefore 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.
normalize-gap
Purpose
Normalize heterogeneous research-gap records into a comparable schema before prioritization or decision operations.
Input contract
yaml
required: [gap_records, gap_schema]
optional: [evidence_records, domain_taxonomy, coding_rules]
constraints: [normalization preserves source wording, uncertainty, and gap type]Procedure
- Map each record to problem, evidence, population, mechanism, and consequence fields.
- Normalize terminology, units, and scope without erasing source distinctions.
- Mark unknown, conflicting, and inferred fields.
- Emit comparable gap records with traceability to originals.
Output contract
yaml
produces: [normalized_gap_records, field_mapping, conflict_log, traceability_map]
delta_fields: [findings, evidence_updates, uncertainties, open_questions]Quality gates
- Every normalized field traces to source text or is marked inferred.
- Conflicting gap definitions remain visible.
Failure and counterexamples
Do not collapse different gaps because they share a label or convert missing evidence into a low-priority score.
Provenance map
resolved: normalize-gap
