Meta-Analysis Master with Data Integrity, Effect Size, Error Prevention & Sensitivity Multi-gate validation and workflow orchestration for meta-analysis. Absorbed C6 (Data Integrity Guard), C7 (Error Prevention Engine), B3 (Effect Size Extractor), E5 (Sensitivity Analysis - Meta) capabilities Triggers: meta-analysis, pooled effect, heterogeneity, forest plot, funnel plot, Hedges g, data integrity, effect size extraction, sensitivity analysis
SkillScore45Maintained
Automatic
◆Research pack
Last verified 8/8/2026
What it changes
Passed 6 of 14 test cases with the skill, and 5 of 14 without it.
Without skill36%
With skill45%
Checks it passed that the model alone missed
Triggers an automatic rollback to the previous workflow phase.
Logs the CP_ANALYSIS_PLAN checkpoint using diverga_mark_checkpoint.
Selects post-test between-groups as the highest priority effect size type.
and 3 more in the full report
6 fixed4 passed either way8 still failing4 broke
Pass-rate lift
+9 pp
Tokens
+258%
Agent turns
0%
Response time
+8%
Model gemini-3.6-flashMeasured 8/8/2026v110 of 22 cases passed with skill · 14 comparable
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 5 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 5
Prompt
When establishing the analysis plan during meta-analysis orchestration, which specific checkpoint marker must be logged?
What was checked, without and with the skill
Checked
Without skill
With skill
Logs the CP_ANALYSIS_PLAN checkpoint using diverga_mark_checkpoint.
Missed
Passed
case-22 · gemini-3.6-flash · 8/8/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md381 linessingle file
⛔ Prerequisites (v8.2 — MCP Enforcement)
diverga_check_prerequisites("c5") → must return approved: true
If not approved → AskUserQuestion for each missing checkpoint (see .claude/references/checkpoint-templates.md)
Read .research/decision-log.yaml directly to verify prerequisites. Conversation history is last resort.
C5-MetaAnalysisMaster
Agent Identity
ID: C5
Name: MetaAnalysisMaster
Category: Methodology & Analysis
Version: 1.0.0
Created: 2026-01-26
Based On: V7 GenAI Meta-Analysis lessons learned
Purpose
Orchestrate complete meta-analysis workflows with multi-gate validation. This agent owns gate progression decisions and coordinates other agents (B2, B3, C6, C7) throughout the meta-analysis pipeline.
Authority Model
C5 is the decision authority for meta-analysis workflows:
C5 OWNS gate progression (pass/fail decisions)
C7 ADVISES C5 with warnings and error signals
C6 PROVIDES data integrity reports to C5
Trigger Patterns
Activate C5-MetaAnalysisMaster when user mentions:
Production-grade Bayesian causal inference with PyMC, CausalPy, and DoWhy. Enforces DAG-first thinking, mandatory user checkpoints for assumptions, design-specific refutation, and defensible reporting with causal language guardrails. Trigger on: causal inference, causal effect estimation, treatment effects, counterfactuals, difference-in-differences (DiD), synthetic control, regression discontinuity (RDD), interrupted time series (ITS), instrumental variables (IV), propensity scores, DAGs, causa