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Glama

Moderate

moderate
Read-only

Safety check of a text or a chat turn with Llama Guard 3: safe or unsafe, and the violated categories (S1 to S14, named in plain words). Send text, or messages (up to 20 turns). Classifies only; it does not change or block anything. Price: $0.002 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Input Schema

NameRequiredDescriptionDefault
textNoText to check, up to 8,000 characters
messagesNoOr chat turns: {role: user or assistant, content}, up to 20

Output Schema

NameRequiredDescriptionDefault
safeNo
modelNo
sourceNo
checkedAtNo
categoriesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations cover only readOnlyHint and openWorldHint, so the description carries real additional weight: it discloses the pricing model ($0.002 USDC per successful call via x402 on Base, Solana or Arc), that failed calls are free, and that the operation is non-mutating ('does not change or block anything'). These are exactly the traits an agent needs before invoking a paid external classifier.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences, front-loaded with what the tool returns, followed by input modes, scope limits, and cost. Every sentence carries information an agent cannot get from the structured fields.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-format detail is unnecessary; the description still supplies the category range and safe/unsafe framing. For a two-param, zero-required paid classifier, nothing needed to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters including the 8,000-character and 20-turn limits. The description restates the 20-turn cap and names the category space but adds no syntax or format detail beyond the schema, which matches the baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Names the specific verb (safety check/moderation), the engine (Llama Guard 3), the resource (text or chat turn), and the precise output taxonomy (safe/unsafe plus S1–S14 categories in plain words). This is distinguishable at a glance from siblings like classify, sentiment, violations, or redact.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

States the two accepted input modes ('Send text, or messages (up to 20 turns)') and explicitly bounds the tool's role with 'Classifies only; it does not change or block anything,' which tells the agent not to expect enforcement. It stops short of naming alternatives (e.g. sentiment/classify) or when-not-to-use conditions, so it does not reach a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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