Act as a senior Monitoring and Evaluation research analyst.

Analyze all uploaded documents concerning [research question].

Identify the main claims and group them by theme.

For each claim:
– State the central finding.
– Identify the sources supporting it.
– Provide page numbers or relevant sections.
– Distinguish empirical evidence from interpretation.
– Identify findings supported by multiple independent sources.
– Highlight claims supported by only one source.

Present the results in an evidence matrix.

Do not assume multiple reports represent independent evidence if they rely on the same underlying dataset.

Review all uploaded evaluation reports concerning [topic].

Identify patterns that appear in at least three documents.

For each pattern:
– Describe the recurring finding.
– Identify the supporting reports.
– Provide supporting passages and page references.
– Explain the relevant evaluation dimension.
– Identify contradictory or exceptional findings.
– Explain possible contextual differences.

Do not force findings into common themes when the evidence does not support a meaningful connection.

Act as a senior Monitoring and Evaluation methodologist.

Examine the conclusions concerning [evaluation question].

Identify the assumptions underlying each major conclusion.

For every assumption:
– Explain what the report assumes.
– Determine whether it is tested or simply accepted.
– Identify evidence supporting or challenging it.
– Explain how the conclusion could change if the assumption were incorrect.
– Recommend additional data or methods to test it.

Pay particular attention to causality, sampling, representativeness, attribution, and indicator validity.

Compare [Evaluation Report A] and [Evaluation Report B] concerning [topic].

Develop a comparative table covering:
– Evaluation objectives and research questions.
– Research design and methodology.
– Sampling strategy and sample size.
– Data collection instruments.
– Indicators and measurement approaches.
– Data analysis methods.
– Limitations and potential biases.
– Main findings and conclusions.

Identify which conclusions have stronger methodological support.

Explain whether differences in findings could result from methodology, context, populations, or reporting periods.

Conduct a critical consistency review of the uploaded reports concerning [topic].

Identify significant contradictions and inconsistencies.

For each inconsistency:
– Quote the relevant statements from both sources.
– Identify the documents and page references.
– Explain precisely what differs.
– Check whether different definitions, indicators, populations, or reporting periods could explain the discrepancy.
– Identify contradictions between numerical tables and narrative interpretations.
– Explain how the discrepancy affects the credibility of the findings.

Do not resolve contradictions through speculation. Distinguish documented explanations from hypotheses.

Review the uploaded evaluation report and classify its major statements into four categories:

1. Empirical findings supported by quantitative or qualitative data.
2. Stakeholder perceptions and opinions.
3. Researcher interpretations and analytical judgments.
4. Claims without sufficient supporting evidence.

For each statement:
– Provide the original quotation.
– Identify its location in the document.
– Explain the type of supporting evidence.
– Assess whether the evidence is sufficient.
– Identify what requires additional verification.

Pay particular attention to causal claims and programme effectiveness.

Act as an independent evaluation quality assurance specialist.

My preliminary evaluation conclusion is:

[Insert your draft conclusion.]

Using the uploaded evidence, identify:
– The strongest evidence supporting the conclusion.
– The strongest evidence challenging it.
– Alternative explanations for the results.
– Methodological weaknesses.
– Evidence gaps.
– Whether the conclusion is proportionate to the available evidence.

Finally, rewrite the conclusion using appropriately cautious language.

Do not exaggerate claims. Distinguish correlation, contribution, and demonstrated causality.

Analyze the uploaded documents in relation to [research question].

Identify the most important unanswered questions and evidence gaps.

For each gap:
– Explain what information is missing.
– Identify why it matters.
– Explain how it limits current conclusions.
– Recommend additional evidence.
– Suggest appropriate data collection methods.
– Recommend relevant indicators or research questions.

Prioritize gaps according to their importance for programme decisions and evaluation credibility.

Review the major findings and rank the five most important according to the strength of their supporting evidence.

Assess:
– Relevance to the evaluation question.
– Quality and reliability of the data.
– Appropriateness of the methodology.
– Consistency across independent sources.
– Degree of triangulation.
– Potential sampling and measurement biases.
– Limitations affecting interpretation.

Assign an evidence assessment:

HIGH: Strong and sufficiently corroborated evidence.
MODERATE: Reasonable evidence with identifiable limitations.
LOW: Limited, inconsistent, or insufficiently verified evidence.

Explain every rating and recommend additional verification where necessary.

These are analytical judgments, not statistical confidence intervals.

Act as a senior Monitoring and Evaluation specialist preparing an analytical report for [organization or donor].

Research question: [Insert research question.]

Prepare a concise evidence-based evaluation conclusion containing:

1. Executive summary.
2. Key findings supported by evidence.
3. Assessment of evidence quality.
4. Areas of agreement and disagreement.
5. Methodological limitations.
6. Alternative explanations.
7. Implications for programme implementation.
8. Evidence-based recommendations.
9. Remaining uncertainties and research priorities.

Requirements:
– Provide citations for every substantive claim.
– Include page references where available.
– Distinguish findings from interpretations and recommendations.
– Do not introduce unsupported facts.
– Do not claim causality without appropriate evidence.
– Acknowledge contradictory evidence.
– Use professional language suitable for senior management and development partners.

End with a statement explaining what decision-makers can reasonably conclude and what remains uncertain.