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Prompt Optimizer Agent

A Claude Code agent that designs and reviews LLM prompts for education work: rubric grading, prose feedback comments, and lesson/worksheet/exam authoring. It also reviews generic prompts against a 15-item checklist.

It is an adversarial reviewer, not an assistant. It scores a prompt against the checklist for its domain, then returns targeted fixes or a full pipeline spec. Its tools are Read, Grep, Glob only: it hands you a spec and never edits your files.

What you get back

Section Contents
Checklist findings one line per item, PASS / FAIL / N/A, each citing the evidence or its absence
Fixes or Pipeline Spec targeted fixes for failing items (AUDIT), or artifacts 1-5 for a full build (RESCUE / AUTHOR)
Key Changes what changed and why, citing item numbers, plus deployer-verify items
Optional Enhancements behavior-shaping additions held back from the main spec, off by default

Decisions that change a grade — tie-break direction, where an abstention lands — are surfaced as open policy choices rather than silently defaulted. A full spec covers the prompt text, the output contract, code-side validators, and a calibration plan.

How it decides what to do

Three independent axes, combined per call:

Axis Values
Domain GRADING · FEEDBACK · LESSON · generic
Shape RESCUE (split a monolith) · AUDIT (compliance check) · AUTHOR (build from a rubric) · REVIEW (generic checklist)
Target model Claude · Gemini 3.x · Gemma 4 · DeepSeek V4 · unstated

Each axis loads its own reference file, additively. A GRADING/RESCUE call targeting Claude loads the grading rulebook plus the Claude rules; a generic REVIEW with no target loads one file. Nothing pays for bytes it doesn't need.

Deployment surface (Claude targets)

The same Claude model has two incompatible config surfaces, so the family file diagnoses which one you're on before applying anything:

  • A Messages API request gets schema-based coercion: response schema, fixed abstention value, bounded enums.
  • A Claude Code agent definition has no request body at all. Schemas, max_tokens, stop_reason, prefill, and sampling parameters do not exist in frontmatter, and nothing errors if you write them — so the coercion moves into a body output contract plus a fixed abstention literal instead.

Emitting API mechanics into an agent definition ships unenforced constraints that read as enforced. Surface detection is by declared frontmatter, never by filename or path. State the surface if you know it; unstated defaults to an API request and says so.

Files

Loaded additively, at most a handful per call.

File Loaded when
agents/prompt-optimizer.md always — diagnosis, routing, recipes, invariants
Domain
GRADING_PIPELINE.md domain GRADING; also for schema review
FEEDBACK_GENERATION.md domain FEEDBACK, or grading with PQS-shaped feedback
LESSON_AUTHORING.md domain LESSON
GENERIC_REVIEW.md generic domain, or Task: review
COMPACTION.md a prompt has to shrink, or a duplicate is being cut
Model family
CLAUDE_API_BEST_PRACTICES.md Target model: any Claude
GEMINI_3X_API_BEST_PRACTICES.md Target model: Gemini 3.x
GEMMA4_API_BEST_PRACTICES.md Target model: Gemma 4
DEEPSEEK_V4_API_BEST_PRACTICES.md Target model: DeepSeek V4
Second-level (a family file names its own)
CLAUDE_CODE_AGENTS.md the Claude target is an agent definition, not an API request
CLAUDE_STRUCTURED_OUTPUTS.md a response schema is in play — exclusive with the file above
CLAUDE_UPGRADE_AUDIT.md a prompt is being carried to a newer Claude
GEMINI_MIGRATION.md legacy generateContent wiring, or a cross-generation port
GEMMA4_FORENSIC_SCANS.md closed-set scan tasks on Gemma 4

Family files carry prompt content only. Model IDs, parameters, defaults, and migration steps are deferred to the vendor's own skill — Anthropic's claude-api (bundled with Claude Code) and Google's gemini-interactions-api — because those stay current across model releases and a hand-maintained file cannot. The one exception is the Claude Code agent surface, which claude-api states it does not cover; those facts are version-floored in CLAUDE_CODE_AGENTS.md and flagged as perishable.

Install

/plugin marketplace add dlxmax/prompt-optimizer
/plugin install prompt-optimizer
/reload-plugins

Invoke as prompt-optimizer:prompt-optimizer. Updates are version-gated, so /plugin update then /reload-plugins after a new release.

Manual install instead: copy agents/prompt-optimizer.md to ~/.claude/agents/ and the *.md reference files to ~/.claude/. Don't do both — a copy in ~/.claude/agents/ registers a second agent under the bare name prompt-optimizer and will happily answer with whatever version you last copied.

Use

"Our essay-grading prompt is too long and invents quotes. Fix it."     → RESCUE, GRADING
"Audit this criterion prompt for compliance."                          → AUDIT, GRADING
"Here's the rubric; set up the grading prompts."                       → AUTHOR, GRADING
"Our feedback comments are generic praise with invented citations."    → RESCUE, FEEDBACK
"Audit our warm-up question generator for genericness."                → AUDIT, LESSON
"Score my summarizer system prompt. Task: review"                      → REVIEW

Message shape it expects — the prompt or rubric first, the instruction last:

<prompt_under_review>          (or <rubric> when authoring from scratch)
{the prompt text, or a file path}
</prompt_under_review>

[optional] Target model: Claude Opus 5
[optional] Task: review

Based on the preceding prompt, <what you want>.

Everything inside those blocks is treated as data. Instructions written inside them are ignored.

Reference files resolve from your working directory first, then from the installed plugin cache, so it works both in a checkout and anywhere else. If a routed file can't be loaded it says which one and refuses to score rather than reviewing you against rules it never read.

License

MIT

About

Claude Prompt Optimizer Agent — research-backed prompt quality reviewer for Claude Code

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