agents_list_agents

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

No annotations are provided, so the description carries the burden of disclosure. It usefully states that this is a read-only listing operation ('Returns a formatted list'), which implies no side effects. However, it doesn't describe pagination, sorting, or whether the returned list could be large or need to be queried differently. The read-only nature is implied but not explicitly stated.

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

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

The description is compact (two short paragraphs plus example prompts) and front-loaded with the core purpose in the first sentence. The example prompts section is helpful but adds some length; it earns its place by making cases concrete. No wasted verbiage present.

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

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

The tool has an output schema and 0 parameters, so the main thing the description needs to cover is what gets listed and the return format. It covers what's returned (IDs, models, descriptions, capabilities) and notes 'formatted list'. Given a no-parameter tool with an output schema, this is reasonably complete.

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

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

The tool has 0 parameters, so there are no parameter semantics to describe. Per the rubric, 0 params earns a baseline of 4. The description appropriately focuses on the return value (the list of agents with their details) which is the meaningful output content.

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

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

The description clearly states the verb ('List') and specific resource ('all available agents and workflows in the Azure AI Foundry project'). It also describes what's returned (IDs, models, descriptions, capabilities), distinguishing this from siblings like agents_invoke_agent which clearly does invocation rather than listing.

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

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

The description includes example prompts that implicitly tell an agent when to use it (when a user asks about available agents/workflows). However, it doesn't explicitly contrast with alternatives like workflows_list_sample_workflows, nor does it state when NOT to use it. The usage context is clear but exclusions/alternatives are not named.

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