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

With no annotations supplied, the description carries the full transparency burden. It discloses the OAuth-style browser authorization flow (private one-hour URL), that credentials are never accepted through MCP, that the job resumes after authorization, and that insufficient evidence triggers a user decision. It does not describe side effects such as artifact creation or lifecycle details, but the core behavioral model is well surfaced.

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 four sentences with no filler: purpose first, then user-interaction requirements, auth behavior, and the insufficient-evidence branch. Each sentence contributes an operational constraint or next step, and the most important scoping information is front-loaded.

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?

Given the tool's complexity (8 parameters, nested objects, no annotations) and the presence of an output schema, the description covers the essential workflow decisions: target selection, profile merge/replace, authorization resumption, and evidence-failure routing. It does not spell out the job lifecycle or explicit relationships to other profile tools, but the output schema and sibling names supply the remaining context.

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?

Schema description coverage is 63%, and the description adds workflow-level meaning beyond the schema for the main parameters: course/target_distance_m (ask user), existing_profile_strategy (merge/replace), and decision (build_anyway/broaden_filters/cancel). It does not elaborate on filters or file-format nuances, but the schema already documents those fields adequately, so the description neither over-explains nor fully compensates for the remaining coverage gap.

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 names a specific verb and resource — 'Build a USRProf from Strava activities selected for a target course or distance' — and immediately conveys the tool's unique source (Strava), distinguishing it from profile-related siblings like generate_runner_profile and validate_runner_profile. The purpose is concrete and actionable.

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?

It gives explicit interaction steps: ask the user for course or distance, ask merge vs replace when an existing profile is supplied, never accept credentials, and resume the same job after authorization. It does not name sibling alternatives or say when not to use this tool, but the decision to use it for Strava-based profiles is clear from the title and source wording.

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