Skip to main content
Glama

get_official_links

Retrieve the canonical official links for Tiramisu AI, including website, support, and documentation when available.

Instructions

Return the canonical list of official links for Tiramisu AI (website, support, docs when available).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations provided, the description carries the full burden. It does convey a read-only intent via 'Return' and nuances availability with 'when available.' However, it does not disclose potential failure modes, empty results, or return format details, leaving some behavioral ambiguity for a tool without annotations or an output schema.

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?

A single, front-loaded sentence that states the action and object without superfluous words. All information is relevant and directly supports tool selection.

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

Completeness4/5

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

For a simple, zero-parameter, read-only tool with no output schema, the description is mostly complete. It states the return type and distinguishes the tool from siblings, but the exact structure of the returned 'list' (e.g., plain strings vs objects with labels/URLs) is not specified, which is a minor gap.

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

Parameters4/5

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

The input schema has zero parameters, so there is nothing for the description to explain. According to the rubric, a zero-param tool gets a baseline of 4, and the description adds contextual value by specifying the scope (Tiramisu AI) and content (website, support, docs).

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?

The description uses a specific verb ('Return') and a clear resource ('canonical list of official links for Tiramisu AI'). It distinguishes the tool from siblings by the data type (links vs overview vs pricing), making its purpose unmistakable.

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?

The description clearly implies when to use the tool (when official links are needed), but it does not explicitly name alternatives or state when not to use it. Since the sibling names are visible in context, the differentiation is clear, but the text itself stops short of explicit 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/rocnubie/tiramisu-ai-mcp'

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