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Skill

/construct-evidence-network

Construct a network-meta-analysis evidence graph and evaluate connectivity/transitivity prerequisites.

From plugin
de-anthropocentric-research-engine
499200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill construct-evidence-network --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/construct-evidence-network

Context preview

The summary Claude sees to decide when to auto-load this skill.

Construct a network-meta-analysis evidence graph and evaluate connectivity/transitivity prerequisites.

SKILL.md

construct-evidence-network.SKILL.md
name: construct-evidence-network
description: "Construct a network-meta-analysis evidence graph and evaluate connectivity/transitivity prerequisites."

construct-evidence-network

Purpose

Construct an evidence graph for network synthesis and evaluate connectivity, transitivity, and comparison support.

Input contract

required: [evidence_records, intervention_nodes, outcome_schema]
optional: [study_designs, effect_sizes, covariate_schema]
constraints: [edges require a shared outcome definition and traceable comparison evidence]

Procedure

1. Normalize interventions, comparators, outcomes, and study-level edges. 2. Build the direct and indirect comparison graph with effect-support provenance. 3. Check connectivity and transitivity assumptions across connected components. 4. Report usable components, unsupported links, and synthesis limitations.

Output contract

produces: [evidence_graph, connected_components, transitivity_assessment, unsupported_links, synthesis_readiness]
delta_fields: [findings, evidence_updates, uncertainties, decisions, open_questions]

Quality gates

  • Every edge points to a study record and outcome definition.
  • Disconnected components are not silently combined.
  • Transitivity judgments list the effect modifiers examined.

Failure and counterexamples

Do not create indirect evidence from incomparable populations or outcomes, and do not treat graph connectivity as proof of exchangeability.

Provenance map

  • `resolved: knowledge-acquisition-evidence-network-construction`
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Ships withde-anthropocentric-research-engine

The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.

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