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

Annotations already mark the tool as read-only and idempotent, and the description adds meaningful behavioral context: the data is the actual indexed code diff on this server, the returned version strings are exact inputs for v1/v2, and custom model grouping semantics (clientGroup) are explained. It also clarifies that this tool exposes real client-specific data rather than public generic knowledge.

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 long but well-structured and front-loaded with the most important instruction (WHEN: ALWAYS call this FIRST). It is organized into trigger phrases, return value detail, and an important exclusion note. Every section adds value, though some repetition of 'actual/THIS server' makes it slightly heavier than necessary.

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?

With no input schema and no output schema, the description carries the full burden, and it succeeds: it explains return shape, exact usage of values as v1/v2 and customModelIds, grouping semantics, precedence over sibling tools, and exclusion of generic tools. Nothing essential is missing for an agent to invoke this correctly.

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 zero parameters, so parameter semantics are largely irrelevant. Baseline 4 applies because there are no parameters to explain, and the description correctly focuses on what the tool returns rather than inputs.

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 tool's job: discover exact D365FO version strings and custom model ids indexed on this server, and explicitly says to call it FIRST before prepare_release_note_context. It distinguishes itself from generic documentation tools and from the sibling prepare_release_note_context.

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?

Usage guidance is explicit and excellent: ALWAYS call this first, with trigger phrases provided, and with an explicit exclusion warning that generic Microsoft Learn/Azure Updates tools must NOT be used for this client-specific purpose. No ambiguity remains about when this tool should be selected.

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