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AI Prompt Library Submission Form

Submit a new AI prompt for steward review with the purpose, target model, input requirements, expected output, and safety notes in one place. Use it to standardize prompt intake before a prompt is approved, reused, or published.

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Overview

The AI Prompt Library Submission Form is a workplace intake form for collecting a proposed AI prompt before it is reviewed, approved, and added to a shared library. It captures the prompt title, submitter, department, target model, exact prompt text, input requirements, expected output, output format, quality criteria, and any safety or policy notes.

Use this template when your organization wants a consistent way to evaluate prompts instead of accepting them through email, chat, or ad hoc documents. It is especially useful when multiple teams are building prompts for the same model, when a steward needs to compare submissions, or when prompts may touch PII, confidential data, or regulated workflows. The form supports clearer review decisions because it separates the prompt itself from the context needed to test it.

Do not use this form as a general AI request intake or a free-form idea box. It is not meant for one-off experimentation with no review path, and it is not the right fit if the prompt will never be reused or governed. If your process does not require steward review, approval tracking, or a prompt library, a lighter request form may be enough. The template works best when the goal is to standardize prompt quality, reduce risk, and create a reusable record of what was submitted and why.

Standards & compliance context

  • Use data minimization principles by collecting only the PII details needed for review, and avoid asking for sensitive data unless the prompt truly requires it.
  • If the prompt may process employee or applicant information, include an accommodation or privacy review path so HR-related use cases can be assessed appropriately.
  • Document any policy or compliance notes in the form so reviewers can create an audit trail of what was submitted, reviewed, and approved.
  • For public-facing or externally shared prompts, confirm that the prompt and its expected output do not create accessibility barriers and can be used in a WCAG 2.1 AA-aware workflow.

General regulatory context for orientation only — verify current requirements with counsel or the relevant agency before relying on this template for compliance.

What's inside this template

Submission Overview

This section identifies the submitter and gives the steward the basic metadata needed to route and track the request.

  • Submission title (required)

    Short name for this prompt submission.

  • Submitted by (required)

    Your name or team name for steward follow-up.

  • Department

    Optional: helps route the submission to the right steward.

  • Submission date (required)

    Automatically captured when the form is submitted.

Prompt Details

This section captures the actual prompt and the context needed to test whether it works as intended.

  • Purpose of this prompt (required)

    Describe the business problem or task this prompt solves.

  • Target model (required)

    Select the model or model family this prompt is designed for.

  • Prompt text (required)

    Paste the exact prompt as it should appear in the library.

  • Required inputs or variables

    Select any placeholders or inputs the prompt expects from the user.

Expected Output and Quality

This section defines what a successful response looks like so reviewers can judge quality consistently.

  • Expected output (required)

    Describe the ideal output format, length, and level of detail.

  • Preferred output format

    Choose the format the model should produce.

  • Quality criteria

    Select the criteria that matter most for this prompt.

Safety, Data, and Review Notes

This section surfaces privacy, policy, and compliance concerns before the prompt is approved or reused.

  • Does this prompt use or generate PII? (required)

    If yes, only include the minimum necessary data and avoid sensitive identifiers unless required.

  • PII details

    Describe what PII is involved and why it is necessary.

  • Compliance or policy notes

    Add any legal, policy, or governance considerations for steward review.

  • Additional review notes

    Include examples, edge cases, or anything the steward should know before approval.

Submission Acknowledgment

This section records that the submitter stands behind the information provided and understands the review process.

  • I confirm this submission is accurate and complete to the best of my knowledge. (required)
  • I understand this prompt will be reviewed before it is added to the library. (required)

How to use this template

  1. 1. Add the submission overview fields so the steward can identify who submitted the prompt, which department it came from, and when it was entered.
  2. 2. Collect the prompt details by asking for the prompt purpose, target model, exact prompt text, and any input requirements needed to run it correctly.
  3. 3. Define the expected output section with the desired output type, formatting rules, and quality criteria so reviewers can judge whether the prompt works as intended.
  4. 4. Include the safety, data, and review notes fields to capture whether the prompt contains PII, what sensitive data is involved, and any policy or compliance concerns.
  5. 5. Add the acknowledgment fields so the submitter confirms the information is accurate and understands the prompt will be reviewed before approval or publication.

Best practices

  • Use a date picker for the submission date and a short text field for the title so the form stays easy to scan and validate.
  • Make the prompt text field large enough for the full prompt, but keep the rest of the form structured so reviewers do not have to parse a wall of text.
  • Use conditional logic to show PII details only when the submitter marks that the prompt contains personal or sensitive data.
  • Ask for the exact target model or model family so reviewers can test the prompt in the environment where it will actually run.
  • Define quality criteria in observable terms, such as tone, completeness, format, and refusal behavior, instead of vague language like "good output."
  • Include a clear note on what happens after submission so employees know whether the prompt goes to a steward, a queue, or an approval workflow.
  • Keep optional fields truly optional and avoid forcing submitters to guess at policy details they do not control.

What this template typically catches

Issues teams running this template most often surface in practice:

The submitter leaves the prompt text too vague, making it impossible to test the prompt against the expected output.
The form does not capture the target model, so reviewers cannot tell whether the prompt is model-specific or portable.
PII is mentioned in the prompt but not documented in the safety notes, which delays privacy review.
Quality criteria are written as subjective preferences instead of concrete output requirements.
The input requirements section is skipped, so reviewers do not know what data the prompt depends on.
The acknowledgment fields are checked without the submitter understanding that the prompt may be revised or rejected.
The form collects unnecessary personal details instead of limiting fields to what the steward actually needs.

Common use cases

Support Operations Prompt Intake
A support operations lead submits a prompt that drafts customer replies from case notes. The steward reviews tone, escalation handling, and whether the prompt avoids unnecessary customer PII.
HR Intake Prompt Review
An HR team member proposes a prompt for summarizing employee requests and routing them to the right queue. The form helps capture accommodation-sensitive language, privacy concerns, and the minimum necessary inputs.
Marketing Brand Voice Library
A marketing specialist submits a prompt that rewrites campaign copy in the company voice. Reviewers can check output format, brand constraints, and whether the prompt is reusable across models.
Operations Reporting Prompt Standardization
An operations analyst shares a prompt that turns weekly metrics into a status summary. The form records the exact inputs, expected structure, and any downstream review notes before the prompt enters the library.

Frequently asked questions

What is this form used for?

This form collects the details needed to review a proposed AI prompt before it is added to a shared prompt library. It captures the prompt purpose, target model, expected output, input requirements, and any PII or policy concerns. That gives the steward enough context to approve, revise, or reject the submission without back-and-forth.

Who should submit a prompt through this form?

Any employee who wants a prompt reviewed for reuse, standardization, or publication in an internal prompt library should use it. It is especially useful for operations, support, HR, marketing, and enablement teams that are building repeatable AI workflows. If the prompt will be used broadly, a steward review helps keep it consistent and safe.

Who should review submissions?

A prompt steward, operations lead, or designated AI governance reviewer should handle the review. In some organizations, legal, privacy, security, or compliance may also need to weigh in when the prompt touches sensitive data or regulated workflows. The form is designed to make that routing easier by surfacing the right review notes up front.

What should be included in the prompt text?

The prompt text should be the exact wording the submitter wants reviewed, not a summary of it. Include any system instructions, user instructions, and placeholders that the model will receive. If the prompt depends on specific inputs or formatting, those requirements should be listed separately so reviewers can test it accurately.

How does this form handle PII or sensitive data?

The form includes fields for whether the prompt contains PII and what kind of data is involved, so reviewers can assess risk before approval. That supports data minimization by making it clear when a prompt should be rewritten to avoid unnecessary personal data. If the prompt uses sensitive information, the review notes can capture any required safeguards or restrictions.

What are common mistakes when using this template?

A common mistake is submitting a prompt without enough context to evaluate output quality, which leads to unclear review decisions. Another is skipping the data and policy notes, especially when the prompt may process customer, employee, or confidential information. It also helps to avoid vague quality criteria like "make it better" and instead define what a good output looks like.

Can this form be customized for different teams or models?

Yes. You can add conditional logic for team-specific fields, model-specific constraints, or approval routing based on risk level. For example, a support team may need fields for tone and escalation handling, while an HR team may need accommodation or privacy prompts. The template is meant to be adapted without changing the core review structure.

How does this compare with collecting prompts in email or chat?

Email and chat make it hard to compare submissions, track review status, or preserve an audit trail of what was approved. This form standardizes the fields reviewers need, which reduces missing information and makes it easier to reuse approved prompts later. It also creates a clearer handoff between the submitter and the steward.

What happens after someone submits the form?

The submission should route to the prompt steward or review queue for evaluation, testing, and approval. If the prompt needs changes, the reviewer can return it with comments or revision requests. If approved, the prompt can be added to the library with its metadata, usage notes, and any restrictions.

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