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

The annotation only declares readOnlyHint=true; the description adds substantial behavioral context beyond that: the tool reads server-local indexed data, version strings are exact and cannot be guessed, and custom models carry a clientGroup tag whose grouping semantics dictate that related models should be passed together. The disclosure that this server holds the ACTUAL indexed code diff and client code is a meaningful behavioral trait that shapes how the agent should trust and sequence this call. Nothing contradicts the readOnly annotation.

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 structured with clear signposts: 'WHEN:', 'Triggers:', 'Returns', 'IMPORTANT:' — and the most critical directive (call FIRST) is front-loaded. Every clause carries new information: trigger phrases, return-value semantics, grouping rules, and tool-exclusion guidance. It earns its length, though the return-value section is a single dense, parenthetical-heavy sentence that could be broken up for readability.

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?

For a 0-parameter, read-only discovery tool with no output schema, the description is complete. It covers when to call, what it returns, how to interpret and chain the returned values, and which alternatives to avoid. No essential decision-making information is missing for an agent to invoke it correctly and use its results.

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?

With zero parameters, the schema provides no semantic content, and the baseline is 4. The description goes beyond that baseline by explaining exactly how the returned values will be consumed as downstream parameters: the exact 'version' string feeds v1/v2, and the model 'id' feeds customModelIds. The concrete format example (10.0.2527.109) and the clientGroup grouping rule add real semantic value that an agent cannot infer from the empty schema.

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 states a precise verb+resource+scope: it 'discovers the exact D365FO version strings and custom model ids actually indexed on THIS server.' It distinguishes itself from the sibling prepare_release_note_context by declaring it must be called FIRST, and from generic documentation-search tools by explaining they lack this server's data. There is no ambiguity about what this tool does.

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 unmissable: 'WHEN: ALWAYS call this FIRST, before prepare_release_note_context.' It provides concrete trigger phrases ('release note', 'compare D365 versions', 'upgrade impact for a client', 'regression risk') and explicit when-not guidance, naming generic Microsoft Learn / Azure Updates / documentation-search tools that must NOT be used. No inference is required from the agent.

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