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2665 P1 Meta Process Capture Expert Panel Dataset Builder Eceaac36
ASecurityDocument the multi-agent expert panel methodology as a reusable system for building datasets that inform skills and systems. The process — assign framework experts to repositories, ask structured questions, cross-examine, synthesize, map to requirements, validate — produced high-quality sourced findings. Capture this as a repeatable pattern.\n**Key elements to document**:\n- Expert assignment protocol (one agent per source repo, source-code-only evidence standard)\n- Question group design (th...
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- Added October 11, 2026
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[](https://www.skillsdirectory.com/skills/tools-only-2665-p1-meta-process-capture-expert-panel-dataset)---
name: Meta-Process Capture — Expert Panel Dataset Builder
description: "Document the multi-agent expert panel methodology as a reusable system for building datasets that inform skills and systems. The process — assign framework experts to repositories, ask structured questions, cross-examine, synthesize, map to requirements, validate — produced high-quality sourced findings. Capture this as a repeatable pattern.\n**Key elements to document**:\n- Expert assignment protocol (one agent per source repo, source-code-only evidence standard)\n- Question group design (themed questions → cross-examination → synthesis)\n- Cross-examination as adversarial validation (experts challenge each other's claims)\n- Phased output (discussion → requirement mapping → synthesis → validation)\n- Traceability chain (claim → expert citation → file:line evidence)\n- Session continuity handling (state file enables cross-session resumption)\n**Input artifacts**: `plugins/plugin-creator/skills/assessor/references/ARL/ARL-agent-instructions.md`, `qa-expert-panel.md`"
metadata:
topic: meta-process-capture-expert-panel-dataset-builder
source: ARL expert panel process (sessions 2026-02-12 to 2026-02-13)
added: '2026-02-13'
priority: completed
type: Feature
status: done
issue: '#90'
plan: ''
---
**Suggested location**: New skill or methodology document — captures the meta-process, not the ARL contentAttribution
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