construct-evidence-network
Construct a network-meta-analysis evidence graph and evaluate connectivity/transitivity prerequisites.
Skill by yogsoth-ai
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/yogsoth-ai-construct-evidence-network
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/construct-evidence-network
What's inside
- Skill name
construct-evidence-network- Description
- Construct a network-meta-analysis evidence graph and evaluate connectivity/transitivity prerequisites.
- License
- Apache-2.0
- Instructions
- 44 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# construct-evidence-network ## Purpose Construct an evidence graph for network synthesis and evaluate connectivity, transitivity, and comparison support. ## Input contract ```yaml 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 ```yaml 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`
From yogsoth-ai/de-anthropocentric-research-engine, Apache-2.0.
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Signals
- Stars
- 505
- Forks
- 43
- Open issues
- 1
- Last commit (this folder)
- Sep 23, 2026 (1 month ago)
- Last release
- Oct 23, 2026 (8 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Move a scientific object up/down in abstraction or narrow/broaden selected scope dimensions (population, mechanism, context, outcome, timeframe, system…
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construct-evidence-network skill. Agent Mart. https://agentmart.dev/skills/yogsoth-ai-construct-evidence-network (last updated 2026-10-24)