Research Comparison Template
A reusable multi-source comparison template with variables for sources, evaluation criteria, audience, decision context, priority criteria, and output format.
Overview
Comparing multiple sources without structure produces averaging — strong sources dominate, nuanced disagreements disappear, and the output is a consensus that none of the sources actually support. This template forces per-source extraction before synthesis, names criteria explicitly, and requires the output to surface contradictions rather than resolve them. The result is a comparison your decision-makers can trust rather than one that just feels comprehensive.
Workflow
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Define evaluation criteria before reading the sources
The evaluationCriteria variable should be set before you read the sources. Criteria defined after reading tend to be shaped by what you found, not by what the decision needs.
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Fill in the template variables
Open in Prompt Template Builder. Variables: sources, evaluationCriteria, audience, decisionContext, priorityCriteria, outputFormat, caveats.
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Label sources consistently
Give each source a clear identifier in the sources variable — title, author, or URL. The model needs these to attribute claims. Unlabeled sources produce unattributed conclusions.
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Focus review on contradictions and gaps
The most valuable output section is the contradictions and evidence gaps. That is where you will find what the available research does not support, which is often more decision-relevant than what it does.
Why This Works
- Per-source extraction before synthesis prevents one strong source from anchoring the entire comparison — weaker sources get the same structured treatment
- Named attribution for every claim makes it easy to trace a conclusion back to its evidence when the decision is challenged
- Explicit contradiction flagging surfaces disagreements that averaging would erase — genuine expert disagreement is information, not noise
- Evidence gap tracking makes the boundaries of what you actually know visible before you make the decision
Best for
- Decisions where source attribution matters — when you need to know which source supports which conclusion
- Topics where expert disagreement is meaningful rather than a rounding error
- Comparisons where criteria need to be consistent across all sources
- Pre-decision analysis where you need a defensible synthesis rather than a personal judgment
Not for
- Single-source analysis — use a summarization template instead
- Real-time research where you cannot paste sources in full
- Sources requiring specialist domain knowledge to evaluate fairly without bias
Use cases
- Comparing vendor proposals or tool evaluations with consistent criteria
- Synthesizing competing research papers before writing a literature review section
- Consolidating stakeholder or user research findings across multiple interview sessions
- Reviewing multiple analyst reports on the same market or technology