iris-interface-field-match
CommunityStreamline semantic normalization and candidate matching for IRIS interface fields.
Software Engineering#semantic analysis#candidate matching#data review#field normalization#IRIS interface
AuthorSkylerCook
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill addresses the need for semantic normalization, candidate matching, and diagnosis of unmatched fields in IRIS interface data, facilitating efficient data processing and review.
Core Features & Use Cases
- Semantic Normalization: Standardize field codes, names, types, lengths, and mandatory flags.
- Candidate Matching: Provide semantic matches, confidence scores, and evidence.
- Unmatched Diagnosis: List reasons for unmatched fields such as missing codes, ambiguous names, type conflicts, and missing local feedback.
- Feedback Draft Generation: Create local feedback drafts for manual review and confirmation.
- Use Case: Ideal for post-processing
iris-interface-doc-ingestoutputs to ensure data quality and accuracy before further analysis or integration.
Quick Start
Execute the skill in the project root directory with the command: python .agents/plugins/iris-interface-dev-plugin/scripts/iris-interface-field-match.py --parsed docs/output/iris-interface/<doc-name>/parsed.json --project-root .
Dependency Matrix
Required Modules
None requiredComponents
scripts
💻 Claude Code Installation
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Please help me install this Skill: Name: iris-interface-field-match Download link: https://github.com/SkylerCook/imedical.agents/archive/main.zip#iris-interface-field-match Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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