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Prompt Quality

GPTClaudeDeepSeek··1,167 copies·updated 2026-07-14
prompt-quality-2.prompt
# Prompt Quality Rubric

Use this rubric when adding or reviewing prompts.

## Required

- The prompt has a specific target platform or assistant class.
- The intended mode is documented: text, voice, API, project, local agent, or other.
- The prompt includes a clear maintenance model for memory, state, or updates.
- The entry has measurable quality checks.
- Known limitations are stated plainly.
- Any persistence instruction explains what is manual, automatic, or simulated.

## Reject Or Revise

Revise prompts that:

- claim durable memory without explaining where memory is stored;
- require unavailable tools without fallback notes;
- include hidden instructions intended to bypass user control;
- include secrets, private data, or unredacted personal logs;
- ask the model to fabricate validation, citations, or results;
- add complexity without a testable benefit.

## Scoring

Use a 0-2 score for each area:

- Purpose clarity.
- Platform fit.
- Portability.
- Validation strength.
- Safety and privacy.
- Maintenance cost.

Prompts scoring below 8 out of 12 should remain draft unless there is a documented reason to publish early.

when to use it

Community prompt sourced from the open-source GitHub repo WhenMoon-afk/persistent-persona-prompts (MIT). A "Prompt Quality" style prompt — adapt the placeholders and specifics to your task. Imported as-is and not independently retested here, so check the output before relying on it.

tags

productivitycommunitydeveloper

source

WhenMoon-afk/persistent-persona-prompts · MIT