> For the complete documentation index, see [llms.txt](https://docs.mozilla.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.mozilla.ai/any-guardrail/api-reference/taxonomy.md).

# Taxonomy

The vocabulary behind guardrail metadata (see the [AnyGuardrail reference](/any-guardrail/api-reference/any_guardrail.md) for the `list_guardrails` / `group_by` query API and [Guardrails](/any-guardrail/api-reference/index.md) for the catalog grouped by primary category).

A machine-readable export of every guardrail's metadata is published at <https://raw.githubusercontent.com/mozilla-ai/any-guardrail/main/schemas/guardrail_metadata.json>.

## GuardrailCategory

What a guardrail is designed to detect (a guardrail may span several).

| Value              | Meaning                                                                        |
| ------------------ | ------------------------------------------------------------------------------ |
| `prompt_injection` | Prompt injection, jailbreak, and instruction-override attempts.                |
| `content_safety`   | Harmful content: violence, sexual, self-harm, dangerous, or criminal material. |
| `toxicity`         | Hate, harassment, and profanity.                                               |
| `pii`              | Personal / sensitive-data detection.                                           |
| `hallucination`    | Groundedness / RAG-faithfulness of a response against provided context.        |
| `off_topic`        | Topical relevance / answer relevance.                                          |
| `bias`             | Social bias / fairness.                                                        |
| `tool_use`         | Function-calling / agent-action validity.                                      |
| `general_judge`    | Open-ended rubric / quality scoring against bring-your-own criteria.           |

## GuardrailStage

Where in a request/response flow a guardrail runs.

A guardrail that screens both the prompt and the response has `stages == {INPUT, OUTPUT}` (there is no separate `EITHER` value). `RAG_CONTEXT` marks guardrails that additionally consume retrieved documents/context.

| Value         | Meaning                                                          |
| ------------- | ---------------------------------------------------------------- |
| `input`       | Screens the user prompt (pre-call).                              |
| `output`      | Screens the model response (post-call).                          |
| `rag_context` | Consumes retrieved documents/context (e.g. groundedness checks). |

## OutputShape

The decision form a guardrail produces (aligns with the populated `GuardrailOutput` fields).

| Value         | Meaning                                                   |
| ------------- | --------------------------------------------------------- |
| `binary`      | A single flagged / not-flagged verdict.                   |
| `multi_label` | Independent per-category scores/verdicts.                 |
| `categorical` | A taxonomy verdict (e.g. Llama Guard S-codes).            |
| `score`       | A scalar risk score.                                      |
| `rubric`      | A judge score against a rubric (e.g. 1-5 / 1-10).         |
| `span`        | Character-offset spans (e.g. hallucination or PII spans). |

## BackendType

How a guardrail executes.

| Value             | Meaning                                                                 |
| ----------------- | ----------------------------------------------------------------------- |
| `local_encoder`   | A local encoder classifier (HuggingFace or encoderfile).                |
| `local_decoder`   | A local decoder LLM (HuggingFace or llamafile).                         |
| `hosted_api`      | A hosted service requiring a key/endpoint.                              |
| `library_wrapped` | A third-party Python library invoked directly (its own optional extra). |


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