Skip to content
Back to skills

Optimize Prompt And Agent Pipelines With Dspy Programs And Evaluators

ASecurity

Use DSPy to define modular LLM programs, metrics, and evaluation sets so an agent can optimize prompts and pipeline behavior with measurable feedback instead of ad hoc prompt editing.

  • 36 stars
  • 0 votes
  • 0 copies
  • 1 view
  • Added June 8, 2026
ai-agentspythongobashgitsecuritydocumentation

Security analysis

A92/100
  • mediumInstalls packages at runtime which could introduce malicious dependencies

Pro shows the line behind each finding and how to fix it

Scanned June 8, 2026

npx -y skills add agentskillexchange/skills --skill optimize-prompt-and-agent-pipelines-with-dspy-programs-and-evaluators --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Optimize Prompt And Agent Pipelines With Dspy Programs And Evaluators?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Optimize Prompt And Agent Pipelines With Dspy Programs And Evaluators
[![Security: A β€” Skills Directory](https://www.skillsdirectory.com/api/skills/agentskillexchange-optimize-prompt-and-agent-pipelines-with-dspy-prog/badge)](https://www.skillsdirectory.com/skills/agentskillexchange-optimize-prompt-and-agent-pipelines-with-dspy-prog)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: "Optimize prompt and agent pipelines with DSPy programs and evaluators"
slug: "optimize-prompt-and-agent-pipelines-with-dspy-programs-and-evaluators"
description: "Use DSPy to define modular LLM programs, metrics, and evaluation sets so an agent can optimize prompts and pipeline behavior with measurable feedback instead of ad hoc prompt editing."
github_stars: 34308
verification: "security_reviewed"
source: "https://github.com/stanfordnlp/dspy"
author: "Stanford NLP"
publisher_type: "open_source_project"
category: "Code Quality & Review"
framework: "Multi-Framework"
tool_ecosystem:
  github_repo: "stanfordnlp/dspy"
  github_stars: 34308
---

# Optimize prompt and agent pipelines with DSPy programs and evaluators

Use DSPy to define modular LLM programs, metrics, and evaluation sets so an agent can optimize prompts and pipeline behavior with measurable feedback instead of ad hoc prompt editing.

## Prerequisites

Python, DSPy, task examples, scoring metric or evaluator, target LLM provider credentials

## Installation

Use the upstream install or setup path that matches your environment:
- pip install dspy
- pip install git+https://github.com/stanfordnlp/dspy.git

Requirements and caveats from upstream:
- DSPy stands for Declarative Self-improving Python. Instead of brittle prompts, you write compositional _Python code_ and use DSPy to **teach your LM to deliver high-quality outputs**. Learn more via our [official docu...

Basic usage or getting-started notes:
- bash
- To install the very latest from main:
- ## πŸ“œ Citation & Reading More

- Source: https://github.com/stanfordnlp/dspy
- Extracted from upstream docs: https://raw.githubusercontent.com/stanfordnlp/dspy/HEAD/README.md

## Documentation

- https://dspy.ai/

## Source

- [Agent Skill Exchange](https://agentskillexchange.com/skills/optimize-prompt-and-agent-pipelines-with-dspy-programs-and-evaluators/)

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.