skill-2-agentic-concern-extraction
CommunityExtract agentic concerns into a structured sheet.
Data & Analytics#automation#yaml-frontmatter#review-analysis#agentic-concerns#verdict-drivers#conclusion-sheets
Authorjinming99
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill automates turning agentic review outputs into a single, structured concern sheet to streamline evidence synthesis and verdict justification.
Core Features & Use Cases
- Structured extraction: pulls decisiveness, major/minor concerns, goals, and decision drivers from review outputs (summary.yaml, review.md, adversarial_brief.md, gates.md, scorecard.md) and preserves provenance.
- Normalization & deduplication: normalizes severities, consolidates duplicates across sources, and records source details for traceability.
- Output formatting: produces an AgenticConcernSheet compliant with the calibration schema for downstream analysis and auditing.
- Use Case: use this when building concern-alignment data for a paper, ensuring consistent representation of concerns and verdict drivers across reviews.
Quick Start
Run the agentic concern extractor on a paper's result directory to produce a structured concern sheet.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: skill-2-agentic-concern-extraction Download link: https://github.com/jinming99/reviewer-under-review/archive/main.zip#skill-2-agentic-concern-extraction Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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