Skip to main content
Glama

aup_well_known_url

Computes the canonical well-known URL for Classroom AI's Acceptable Use Policy, returning the path /.well-known/ai-aup.json for a given origin.

Instructions

Compute the canonical Classroom AI AUP well-known URL: /.well-known/ai-aup.json.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
originYes
Behavior3/5

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

The description implies a safe, read-only computation with no side effects. However, without annotations, it lacks details on error behavior, idempotency, or any special requirements.

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

Conciseness3/5

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

Extremely short, which is good for conciseness, but it omits crucial information about the parameter and return value. It could be improved with minimal additions.

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

Completeness2/5

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

Even for a simple tool, the description lacks completeness by not explaining the parameter's role or what the output looks like. With no output schema, the description should at least hint at the return format.

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

Parameters2/5

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

The only parameter 'origin' is not described at all. With 0% schema coverage, the description should explain how origin affects the result, but it only gives the static URL path.

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

Purpose4/5

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

Clearly states the tool computes a specific well-known URL and provides the exact path. However, it does not differentiate from sibling tools like aup_fetch or aup_validate, which could be confusing.

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

Usage Guidelines2/5

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

No guidance on when to use this tool vs alternatives such as aup_fetch or aup_validate. The description does not specify context or exclusions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mizcausevic-dev/mcp-kinetic-gain'

If you have feedback or need assistance with the MCP directory API, please join our Discord server