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Every team in Alethia gets a Prompt Library — a structured catalog of test prompts grouped into categories. When you run a test, this is where the prompts come from. The library is shared across all projects in the team. So if Project A tests GPT-4o and Project B tests Claude, they’re both pulling from the same pool — which is what makes their results directly comparable.

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What’s in the library by default?

When your team is created, Alethia seeds 18 top-level safety categories with 137 subcategories between them. These cover the major LLM safety domains aligned with EU AI Act risk areas.
The default categories are seeded as empty containers. You add your own prompts to them — or use the optional bulk-import templates Alethia provides.

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Adding your own prompts

You can add prompts one at a time, or upload many at once.

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One at a time

1

Open the Prompts tab

Inside any project, or under Team → Prompt Library.
2

Pick a category

Click into the category (and subcategory, if any) where the prompt belongs.
3

Click 'Add Prompt'

Fill in the form:
  • Name — a short label
  • Content — the actual prompt text
  • Severity — low / medium / high / critical
  • Author — who wrote it (auto-filled, can be overridden)
4

Save

The prompt is immediately available to every project in the team.

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Bulk upload

For large prompt sets, upload a JSON file.
1

Click 'Bulk Upload'

From the Prompt Library page.
2

Pick the file format

You can upload either a single-prompt file or a multi-prompt file. Alethia auto-detects the shape.
3

Drop your JSON files

You can select multiple files at once. Each file becomes one or more prompts.
4

Review and confirm

Alethia shows you a preview of what will be imported. Categories will be created if they don’t already exist.

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Single-prompt file shape

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Multi-prompt file shape

You don’t need to pre-create categories. If the file references a category that doesn’t exist, Alethia will create it for you (with the matching parent category if you provide a subCategory).

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Generate prompts with AI

Writing adversarial prompts by hand is slow. Alethia can have an LLM draft them for you — either fresh prompts for a category, or jailbreak variants of a prompt you already have. Everything an AI produces lands in a review queue first, so nothing reaches your library until a human approves it.
You need a generator model configured first. In Organization → LLM Configurations, add or edit a model and tick Generator model. See LLM Configurations.

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Generate new prompts

1

Click 'Generate' on the Prompts page

Opens the generation dialog.
2

Set the options

  • Category — which category to generate for
  • Count — how many prompts (up to 10 per run)
  • Severity — target a level, or leave on Auto
  • Language — the language to write the prompts in
  • Guidance (optional) — free-text steering, e.g. “focus on indirect prompt injection via embedded instructions”
3

Generate

The candidates are created and waiting in the review queue.

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Mutate an existing prompt

Mutation takes one of your prompts and rewrites it using attack techniques — different ways adversaries try to slip past a model’s guardrails.
1

Click the ✨ Mutate action on a prompt row

2

Pick one or more techniques

Role-play, hypothetical framing, persona override, encoding/obfuscation, payload splitting, language switch, prompt injection, refusal suppression, and context overload.
3

Set variants per technique, then Mutate

Each technique produces the requested number of variants, all sent to the review queue.

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The review queue

1

Open 'Review queue'

The button shows a badge with the number of pending candidates.
2

Review each candidate

You’ll see the prompt text, its severity, and (for mutations) the technique and the model’s rationale.
3

Accept, edit, or discard

Accept adds it to the library (tagged ai-generated); discard drops it. You can also Accept all or Discard all at once.
AI-generated prompts are adversarial test probes meant only for authorized safety testing. They are quarantined in the review queue and never enter your library — or run against any model — until a person on your team accepts them.
Generation costs tokens only when the generator model uses a team-provided key. If the generator runs on your own API key, there’s no token cost.

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Editing and deleting prompts

Hover over any prompt row to reveal the Edit and Delete actions. Sorting and tooltips on the table make it easy to scan large libraries — hover the prompt name to see the full prompt content.
Editing a prompt does not affect tests that have already run. Past test runs reference the prompt as it was at the time of execution. Future tests will use the new content.

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Why is the library team-scoped, not project-scoped?

This is intentional. If each project had its own prompts, you couldn’t fairly compare two projects (“did GPT-4o do better because it’s safer, or because it had easier prompts?”). By sharing prompts across the team, every project in the team is judged on the exact same questions — making comparisons meaningful. If you genuinely need a totally different prompt set for a different purpose, create a new team.