# Prompt Optimizer

Creates, optimizes, and iteratively refines agent prompts, system prompts, developer...

- Repository: https://github.com/getsentry/skills (1107 stars)
- Category: AI and agents
- License: Apache-2.0
- Last updated: 2026-10-26
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add getsentry/skills --skill prompt-optimizer -g -a claude-code -y`
Codex: `npx skills add getsentry/skills --skill prompt-optimizer -g -a codex -y`
Cursor: `npx skills add getsentry/skills --skill prompt-optimizer -g -a cursor -y`
Gemini CLI: `npx skills add getsentry/skills --skill prompt-optimizer -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add getsentry/skills`

## Description

Creates, optimizes, and iteratively refines agent prompts, system prompts, developer prompts, and reusable prompt templates. Use when asked to improve a prompt, optimize a system prompt, rewrite an agent prompt, tune prompt wording, make a prompt more reliable, port prompts between OpenAI, Claude, or Gemini, or build prompt evals.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Prompt Optimizer

Optimize prompts with evals. Keep every instruction, example, and external context reference causal.

## Load Only What You Need

| Need | Read |
|------|------|
| New prompt | `references/core-patterns.md`, `references/model-family-notes.md`, `references/transformed-examples.md` |
| Existing prompt | `references/meta-optimization-loop.md`, `references/core-patterns.md`, `references/model-family-notes.md` |
| Model-family port | `references/model-family-notes.md`, `references/core-patterns.md` |
| Repeated failures | `references/meta-optimization-loop.md`, `references/core-patterns.md` |
| Weak or ambiguous draft | `references/transformed-examples.md` |
| Provenance | `SOURCES.md` |

## Step 1: Capture Contract

Record before editing:

- task type: new, refine, port, or debug
- target model family and snapshot, if known
- prompt surface: `system`, `developer`, `user`, tool descriptions, examples, schemas
- layer owners: platform, deployer/persona, retrieved context, user payload
- objective and non-goals
- inputs, tools, and external files available
- required output shape
- success criteria and failure cases
- hard constraints: latency, verbosity, safety, budget, tool use, style

If success criteria or examples are missing, create a small eval set first.
If the bottleneck is model choice, retrieval, tool schema, or missing evals, say so before rewriting.

## Step 2: Inventory External Context

For repo or agent prompts, list stable context by exact path:

| Context type | Examples |
|--------------|----------|
| Agent rules | `AGENTS.md`, `CLAUDE.md` |
| Specs | `specs/*.md`, `docs/api.md` |
| Policies | `SECURITY.md`, `docs/releasing.md` |
| Examples | `examples/`, `tests/fixtures/` |

Rules:

- Reference stable files by repo-relative path instead of copying them.
- Paste only excerpts needed for the prompt or eval case.
- Mark whether a file is `loaded`, `referenced`, or `out of scope`.
- Avoid vague context pointers such as "read the docs".

The rest: https://github.com/getsentry/skills/blob/HEAD/skills/prompt-optimizer/SKILL.md