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Run3 multi hop evidence extraction

Skill cxcscmu/SkillLearnBench/skills/b3-teacher-feedback-claude-haiku-4-5/enterprise-information-search/run3_multi-hop-evidence-extraction

Extract evidence from all three tiers (explicit reviewers, substantive feedback contributors from Slack and transcripts, and other identifiable contributors). Follow artifact references and traverse relationships to collect complete answer sets.From its SKILL.md

Install
npx -y skills add cxcscmu/SkillLearnBench --skill run3_multi-hop-evidence-extraction

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SKILL.md

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Multi-Hop Evidence Extraction Skill

Step 1: Tier 1 - Explicit Reviewer/Approver Fields

  • Locate explicit "reviewers", "approvers", "assigned_to" fields in artifacts
  • Extract all names/IDs listed
  • Track the source field name for each person

Step 2: Tier 2 - Substantive Feedback Contributors

  • Search artifact for linked Slack conversations and meeting transcripts
  • For Slack replies: Extract names of people who provided substantive feedback or comments
    • Do NOT include people who merely reacted or said "thanks"
    • Include people who asked questions, suggested changes, or provided critique
  • For meeting transcripts: Extract names of people who:
    • Actually spoke in the transcript (check dialogue)
    • Provided substantive feedback, suggestions, or decisions
    • Do NOT include people listed only in a participants array without speaking

Step 3: Multi-Hop Reference Traversal

  • For each extracted person/artifact, check if they reference other artifacts or people
  • Follow "related_artifacts", "depends_on", "references" links
  • Recursively extract reviewers from referenced artifacts
  • Traverse up to 3 hops to catch indirect relationships
  • Track the traversal path for validation

Step 4: Tier 3 - Other Identified Contributors

  • Identify any other people who contributed (authors, editors, signers)
  • Exclude people already captured in Tiers 1-2
  • Only include if they have a substantive role

Step 5: Deduplicate and Return

  • Remove duplicates across all three tiers
  • Return as a list of unique names/IDs
  • Document which tier each person came from (for debugging)

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