slack_user

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

With no annotations provided, the description must carry the full behavioral transparency burden. It discloses one side effect—'include_custom_fields... costs one extra API call'—which is valuable. However, it does not mention whether the operation is read-only, require any special permissions, or how it handles invalid identifiers or missing profiles, leaving gaps in the behavioral picture.

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 cleanly structured: a one-sentence purpose, a brief 'Use this to' paragraph, and a two-item Args list. Every sentence adds value, there is no redundant jargon, and the most important information is front-loaded. It is concise without being under-specified.

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 fairly simple lookup tool with only two parameters and an output schema present, the description covers purpose, usage, and parameter semantics well. It omits minor details like error behavior or case sensitivity, but overall it provides enough context for an agent to correctly select and call the tool, especially with the existing output schema.

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 input schema has no descriptions for its parameters (0% coverage), so the description is the sole source of parameter meaning. It fully compensates by explaining name_or_id accepts 'Username, @username, display name, or user ID' and describing include_custom_fields as resolving custom profile fields to labels with an extra API call cost. This goes well beyond the schema's bare property names.

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 opens with 'Resolve a username or user ID to a profile,' which precisely states the action (resolve) and resource (profile). It also provides concrete use cases (converting raw user IDs to names, looking up title/timezone/custom fields), clearly distinguishing it from sibling tools like slack_search or slack_channel_history which focus on different resources or actions.

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 explicitly says 'Use this to turn a raw user ID from another result...' and outlines specific scenarios, giving clear context for when to invoke the tool. It does not name alternatives or state when not to use it, but the usage context is strong enough to guide an agent without confusion.

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