All Rubrics 76

Score how well a deliverable links its data, indicators, or findings to specific decisions across five dimensions using AI. Use to assess MEL plans, indicator reference sheets, monitoring briefs, evaluation reports, learning agendas, and any deliverable that should drive action rather than only describe state.

Score the assumptions column of a logframe for completeness, testability, and link to causal logic. Paste the logframe to assess whether assumptions are doing their analytic job. Use this for the logframe or results framework column; for the assumptions section of a Theory of Change narrative see toc-assumptions-quality.

Score the means of verification (MoV) column of a logframe for source specificity, method appropriateness, and frequency clarity. Paste the logframe to assess whether the MoV column will guide data collection.

Score a logframe across five dimensions using AI. Paste your logframe into the prompt to get a structured quality assessment with dimension scores, evidence citations, and priority revisions.

Score the data flow diagram inside a MEL plan for completeness, role clarity, and feasibility. Paste the diagram (or its narrative description) to get a structured assessment with revision priorities.

Score the learning questions section of a MEL plan for strategic relevance, answerability, and decision-linkage. Paste the section to assess whether questions will drive learning that informs program adaptation.

Score a Monitoring, Evaluation and Learning plan across five dimensions using AI. Paste your MEL plan to get a structured quality assessment with dimension scores, evidence citations, and priority revisions.

Score the roles and responsibilities matrix inside a MEL plan for completeness, specificity, and feasibility. Paste the matrix to assess whether every M&E function has named ownership.

Score a Theory of Change across five dimensions using AI. Paste your ToC narrative or diagram description to get a structured quality assessment with dimension scores, evidence citations, and priority revisions.

Score the causal logic of a theory of change in five dimensions using AI. This is a focused component rubric for the causal pathway only, useful when a ToC is embedded in a logframe, MEL plan, contribution analysis, or adaptive management memo. For a holistic assessment of a complete ToC document including stakeholder engagement and presentation, use the theory-of-change-assessment rubric instead.

Score the assumptions section of a Theory of Change. Paste the assumptions to assess whether they are stated explicitly, testable, prioritized, and connected to specific causal links. Use this for the ToC narrative assumptions section; for the assumptions column of a logframe or results framework see logframe-assumptions-column.

Score whether the causal pathway in a Theory of Change covers the full logic from inputs to impact. Paste the ToC to assess gaps, jumps, and missing intermediate steps.

Score the baseline values and targets attached to indicators for plausibility, evidence basis, and ambition calibration. Paste the indicator with baseline and target to assess whether the numbers are defensible.

Score the design of a composite or index indicator for component selection, weighting logic, and transparency. Paste the indicator definition to assess construction quality.

Score data disaggregation quality across the full data pipeline (planning, collection, analysis, reporting, use) using AI. Applies to MEL plans, indicator frameworks, surveys, evaluation reports, donor progress reports, and monitoring briefs where data should be disaggregated.

Score whether indicators align with the required donor framework (FFP, USAID, DAC, etc.). Paste your indicator set with the target donor's framework named.

Score any indicator or set of indicators in any M&E document (logframes, MEL plans, PIRS, indicator reference sheets, results frameworks) for SMART criteria, definition clarity, disaggregation, source documentation, and indicator family coherence using AI.

Score whether the means of verification (data source plus collection method) named for each indicator are appropriate, specific, and feasible. Paste the indicator with its MoV to assess source-method fit.

Score just the wording of an indicator statement for clarity, precision, and unit specification. Paste the indicator statement to get a focused diagnostic on language quality.

Score whether indicators are correctly classified at output, outcome, or impact levels. Paste indicators to identify mis-classifications that obscure the results chain.

Score the justification for using proxy indicators. Paste the proxy indicator and its rationale to assess whether the proxy-to-outcome link is defended and bounded.

Score one or more indicators specifically against the SMART criteria (Specific, Measurable, Achievable, Relevant, Time-bound). Paste the indicator(s) to get a per-criterion assessment with revision suggestions.

Score a focus group discussion guide across five dimensions using AI. Paste your guide to get a scored assessment of question design, structure, ethics, research alignment, and facilitator guidance. Use when reviewing an FGD guide as a standalone document or embedded in an inception report, evaluation design, or needs assessment.

Score the probe questions in a Focus Group Discussion guide for depth, neutrality, and sequencing. Paste the FGD guide to assess whether probes will surface meaningful insight.