Hire an AI prompt version and test planner

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• A clear version of your prompt
• A score for each version against your test cases
• A winning version, saved with its tests
• Rules for naming versions, checking changes, trying them on part of the work and rolling back

How it does the job well

• Clarify the purpose, audience and limits, such as length, format and deadline, first.
• Use the user's materials and voice. Ask for samples when tone matters.
• Be specific and concrete. Cut what does not serve the purpose.
• Say what you are unsure of and where to check it.

Mistakes it avoids

• Generic output that ignores the user's details.
• Inventing facts, quotes or sources.
• Long answers when a short one was asked for.

What a good result looks like

An example, not your task: A prompt gives good answers one day and weak ones the next.

• Rebuilt prompt. One clear prompt, with a note on what was added or cut.
• Test case pause. Your 10 to 20 test cases, each with an answer you would accept.
• Scores. A baseline score, a score for each version, what each change did and the best version.
• Version 1 save. Your chosen best version, saved in a file with its test cases beside it.
• Version rules. Where prompts live, how versions are named, a check before each change, a small trial and rollback steps.
• HAND-BACK SUMMARY. Each step's file, any step not run, and every MISSING line in one list.

How the work is checked

• Each step passed its own checks, or the run stopped at the step that failed and says why.
• The steps ran in order, and each one used the result of the one before.
• Nothing was invented to fill a gap. Every gap is a MISSING: line.
• Nothing was sent, published or paid for without a clear yes.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

Capabilities

• Rebuild the rough prompt. Works out what the prompt is for, picks a fitting structure, adds the missing context, format and limits, and returns one clean prompt.
• Pause, then write your test cases. You write 10 to 20 cases, each with an answer you would accept. Cases that failed before are the most useful.
• Score each version on the tests. Takes a baseline score, changes one thing at a time, and keeps only the changes the scores support.
• Pause, then save version 1. You pick the best version and save it in a file with its test cases beside it.
• Set up versions and safe changes. Sets where prompts live and how versions are named, a check that runs before each change, a small trial for new versions and a rollback.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id tune-a-prompt-with-real-tests-then-ship-it-with-versions only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/tune-a-prompt-with-real-tests-then-ship-it-with-versions/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• The rough prompt
• What a good answer looks like and who reads it
• Examples of answers that went wrong (optional)
• Where the prompt lives and who edits it (optional)

Functions and deliverables

• Prompt version and test planner: Share your prompt, task and examples. Get a clearer draft, test cases, observed comparisons where tools allow and a version record.
  • A clear version of your prompt
  • A score for each version against your test cases
  • A winning version, saved with its tests
  • Rules for naming versions, checking changes, trying them on part of the work and rolling back
• Prompt editor: Turn a rough request into a clear prompt for any AI. Give it your idea and get a prompt improver result you can paste and use right away.
  • A polished prompt ready to paste
  • Fitting structure for the task
  • Questions only if something key is unclear
  Source: sickn33.
• Prompt tester and tuner: Test a prompt against examples. Get scores for each version and a revision to review.
  • Baseline score
  • Scores for each new version
  • An improved prompt, with a pass or fail result per test case from your own runs
  • Token and cost estimate
  Source: Alireza Rezvani.
• Prompt change manager: Set up prompt versioning, tests and rollback for AI features already live. Get a prompt registry, eval plan and safe deploy steps for your team.
  • Prompt registry design
  • Versioning rules
  • Evaluation pipeline plan
  • A/B test and rollback process
  Source: Alireza Rezvani.
• me.md builder: Answer a few questions, or let your AI use what it remembers. Get one private file that tells any AI who you are.
  • One me.md file with up to ten dated sections
  • A list of facts taken from memory, for you to check
  • A short note of what it removed for privacy
  • The two next steps, to save it and set it up

Tasks you can use it for

• A prompt gives good answers one day and weak ones the next.
• Several people edit the same prompt and you cannot tell which edit hurt.
• A prompt runs in a product or a weekly routine, and a bad answer costs you.

Limits to check before starting

• You will use the prompt once and want a quick rewrite: use the Prompt editor on its own.
• You have no way to judge a good answer yet: write down what good looks like first, or ask a teammate who reads the answers.
• You only want rules for editing a prompt you already tested: use the Prompt change manager on its own.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Download the handoff pack. It holds HANDOFF.md and the 3 skill files in the order they run: Prompt improver, Prompt tester and tuner, and Prompt change manager.
• Give the folder to Claude (in Claude Code, or as files in a Claude Project) and say "Follow HANDOFF.md".
• Paste the rough prompt and say what a good answer is.
• When it pauses, write 10 to 20 test cases with the answer you would accept. Include two or three where it failed before.
• After the scores, save the best version as version 1 in a file, with the test cases beside it.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/tune-a-prompt-with-real-tests-then-ship-it-with-versions for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.