program-evaluation

Design and implement formative, summative, and developmental evaluations using logic models and mixed methods

509 stars

Best use case

program-evaluation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Design and implement formative, summative, and developmental evaluations using logic models and mixed methods

Teams using program-evaluation should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/program-evaluation/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/social-sciences-humanities/social-sciences/skills/program-evaluation/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/program-evaluation/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How program-evaluation Compares

Feature / Agentprogram-evaluationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Design and implement formative, summative, and developmental evaluations using logic models and mixed methods

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Program Evaluation Skill

Design and implement rigorous evaluations of social programs and policy interventions using established frameworks.

## Overview

The Program Evaluation skill enables design and implementation of formative, summative, and developmental evaluations using logic models, theory of change frameworks, and mixed methods approaches for assessing program effectiveness and informing improvement.

## Capabilities

### Evaluation Design
- Formative evaluation
- Summative evaluation
- Developmental evaluation
- Impact evaluation
- Process evaluation

### Logic Models
- Theory of change development
- Input-output mapping
- Outcome identification
- Assumption articulation
- Indicator specification

### Data Collection
- Multiple data sources
- Quantitative measures
- Qualitative methods
- Mixed approaches
- Participatory methods

### Analysis and Reporting
- Outcome measurement
- Attribution assessment
- Cost-effectiveness analysis
- Stakeholder reporting
- Recommendation development

### Utilization Focus
- Stakeholder engagement
- Use identification
- Findings translation
- Recommendation implementation
- Learning facilitation

## Usage Guidelines

### When to Use
- Assessing program effectiveness
- Improving interventions
- Supporting decision-making
- Demonstrating accountability
- Building evidence base

### Best Practices
- Engage stakeholders early
- Clarify evaluation questions
- Use multiple methods
- Consider context
- Focus on utilization

### Integration Points
- Causal Inference Methods skill
- Mixed Methods Integration skill
- Policy Communication skill
- Quantitative Methods skill

## References

- Program Evaluation process
- Policy Impact Assessment process
- Cost-Benefit Analysis process
- Program Evaluation Specialist agent

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