--- name: nonprofit-rbm-logic-model-2c869fb5771e description: Build donor-ready Results-Based Management (RBM) logic models for nonprofit and non-governmental organization (NGO) programs with a 5-level results chain, Theory of Change, Specific-Measurable-Achievable-Relevant-Time-bound (SMART) outcome indicators, Sustainable Development Goals (SDG) alignment, and practical monitoring plans for grant design, implementation, and reporting aligned with United States Agency for International Development (USAID), United Nations (UN), and European Union (EU) requirements. --- # Nonprofit Results-Based Management (RBM) Logic Model ## Goal Produce a complete, donor-ready Results-Based Management (RBM) logic model that clearly links resources to long-term change and includes measurable indicators and monitoring guidance. ## Workflow 1. Gather core context before drafting: - Program problem and intervention summary - Target population and inclusion priorities - Geography and implementation scope - Time horizon (for example, 1 year outcomes vs 3-5 year impact) - Donor/reporting constraints (United States Agency for International Development (USAID), United Nations (UN), European Union (EU), internal template) - Baseline availability and data constraints 2. Ask up to five high-leverage clarifying questions when critical context is missing. If details remain unknown, proceed with explicit assumptions. 3. Build a five-level logic model: - Inputs - Activities - Outputs - Outcomes (short/medium term changes) - Impact (long-term societal/system change) 4. Keep causal logic explicit and testable: - Avoid listing activities as outcomes - Avoid describing deliverables as impact - Use concrete, time-bound outcome statements where possible 5. Define indicators for each outcome: - Provide 3-5 Specific-Measurable-Achievable-Relevant-Time-bound (SMART) indicators per outcome - Include definition/formula, baseline, target, frequency, and data source - Include disaggregation guidance (for example sex, age, location) when relevant 6. Map outcomes and impact to relevant Sustainable Development Goals (SDG) goals and targets only when there is a defensible link. 7. Propose a practical data collection plan: - Baseline and endline timing - Routine monitoring frequency - Follow-up windows (for example 3/6/12 months) - Data quality checks and accountability owner 8. Return output in the required format. ## Output Format 1. Theory of Change (if/then statement plus causal pathway and key assumptions) 2. Executive Summary (2-3 sentences) 3. Logic Model Table (Inputs to Impact) 4. Outcome Indicators (group by outcome) 5. Sustainable Development Goals (SDG) Alignment (goal and target references) 6. Data Collection Plan (method, frequency, owner) 7. Assumptions and Risks (recommended when uncertainty exists) ## Quality Rules - Prefer numeric targets and time bounds over vague language. - Distinguish outputs from outcomes: - Outputs are products/services delivered. - Outcomes are changes in behavior, conditions, or systems. - Keep impact long-term unless user requests a shorter horizon. - State assumptions explicitly for any inferred values. - Flag missing baseline data and suggest how to collect it. ## Reference Usage Use `references/rbm-framework.md` when you need: - Indicator templates - Sector-specific indicator ideas - Sustainable Development Goals (SDG) mapping shortcuts - A complete worked example --- Source attribution: meghal86 Original project: https://github.com/meghal86/stacksignal/blob/54afe4b75ed2eb8f0feabb2f5b57dfa4bcbb3c44/.agents/skills/nonprofit-rbm-logic-model/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2026 vassiliylakhonin Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: meghal86 Original project: https://github.com/meghal86/stacksignal/blob/54afe4b75ed2eb8f0feabb2f5b57dfa4bcbb3c44/.agents/skills/nonprofit-rbm-logic-model/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Education & Research, Project & Program Management Roles: Data Analyst, Program Manager, Project Manager, Researcher Specialties: Specialty not specified Tools: Tool not specified Country applicability: United States Classification basis: Source catalog labels Instruction SHA-256: f05ea2af68a461edbfb975379c5230b428f61c9ae8f971a5cf994f547d0cb2a1