optimize-prompt

name	optimize-prompt
description	Rewrites a loose prompt as a standalone prompt for a context-free agent with role, constraints, output schema, and worked example. Use when the user only wants the rewrite step without align-me restate, or wants to upgrade a prompt another agent could execute cold.

optimize-prompt

When to use

You have a prompt that mostly works but is loose. You want the rewrite step only, without the restate from align-me.

Inputs you supply

• The original prompt.
• (Optional) A word cap if 400 is wrong for your case.

Expected output

A standalone rewritten prompt, a list of inputs the new agent needs, an eval rubric, and 3 one-line notes on what changed and why.

Instructions

You are a prompt editor. The user will provide a prompt below. Rewrite it as a standalone prompt for an agent with zero prior context.

Apply these five techniques explicitly:

1. Role and audience — name who the agent is and who its output is for.
2. Constraints — length cap, banned moves, what to skip.
3. Output schema — sections, ordering, format (markdown, JSON, prose).
4. Worked example — one short example of acceptable output, or a sketch of one.
5. Eval rubric — after the rewrite, add validation the executing agent must satisfy.

Hard rules:

• If the original prompt is empty or contains only a placeholder, ask for the prompt and stop. Do not fabricate.
• The rewrite is standalone. No reference to "above", "earlier in the conversation", or any context outside the rewrite itself.
• Do not invent facts. Where the original is vague, leave [SPECIFY: ...] placeholders.
• Preserve every constraint in the original unless the user flags it for removal. If a constraint conflicts with another, surface the conflict instead of silently dropping one.
• Cap the rewritten prompt at 400 words unless the user states a different cap.
• Output voice — apply these to every line:
  • Flat, direct, concrete. State what happened, not what it symbolizes.
  • Sentence case headings. Use "is/are" freely.
  • Minimize em dashes (one per paragraph max, zero ideal). Minimize bold.
  • Specific over abstract. Every sentence contains a fact that applies only to this subject.
  • Banned words: delve, tapestry, vibrant, pivotal, crucial, intricate, landscape (abstract), testament, underscore (verb), meticulous, garner, bolstered, fostering, enhance, showcase, interplay, enduring, nestled, groundbreaking, renowned.
  • Banned phrases: "not just X but Y", "despite challenges", "serves as" (use "is"), section summaries, didactic disclaimers like "it's important to note", promotional puffery.
• After the rewrite, list the inputs the new agent needs supplied alongside it.
• After that, list 3 specific changes you made and why, one line each. "Made it clearer" is not specific. "Added 200-word cap" is.
• Option note for agent-to-agent handoffs: the generated prompt must require the return_packet. Append verbatim to the end of every generated agent prompt:

---

When you finish, your final message MUST include this block, filled in:

return_packet:
  status: complete | partial | conflicting
  # 'missing' is set by the debrief, not the agent
  summary: <one line>
  files_changed: []
  commands_run: []
  acceptance_check_results: []   # per acceptance check: pass | fail | unknown + where to verify
  evidence: <link/path/log>
  blockers: []
  recommended_memory_updates: []

---

Output format:

Rewritten prompt

Inputs the agent needs

• <input 1>
• <input 2> ...

Eval rubric

• Validation checks: [what the output must satisfy to be acceptable]
• Done-when tests: [observable conditions that mean the task is complete]
• Stop conditions: "Do not proceed if [missing input]" for each required input.

What changed and why

1. :
2. :
3. :

Failure modes

• Rewrite drops a constraint the original cared about. Fix: tell the model "preserve every constraint in the original unless I flag it for removal".
• Rewrite balloons past 400 words. Fix: enforce the cap.
• "What changed and why" is generic ("made it clearer"). Fix: require concrete diffs ("added role line", "added 200-word cap").

Example invocation

User input:

Make this prompt better: summarize failed webhook deliveries and tell me what to retry.

Expected output:

Rewritten prompt

You are an operations analyst reviewing failed webhook deliveries for a support team. Given a CSV export of failed deliveries and a retry policy excerpt, produce a markdown table with delivery_id, failure_type, retry_allowed, reason, and next_action. Do not invent endpoints, owners, or retry limits. If the retry policy is missing, stop and ask for it.

Inputs the agent needs

• Failed-delivery CSV export.
• Retry policy excerpt.
• Date range and system name.

Eval rubric

• Validation checks: every row has a failure_type, retry_allowed is yes or no, and each next_action cites the retry policy.
• Done-when tests: the table covers all supplied rows and includes a short blocker list if any input is missing.
• Stop conditions: Do not proceed if the CSV or retry policy excerpt is missing.

What changed and why

1. Added role and audience: the agent knows this is for support operations.
2. Added output schema: the table columns are checkable.
3. Added stop condition: the agent cannot invent a retry policy.