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

Annotations already declare a safe read-only, closed-world operation, so the bar is lower. The description still adds real behavior: cursor pagination semantics for 'sets' ('next_cursor; keep every other argument the same'), the partial-week caveat, and that fuzzy name matching requires checking meta.resolution in the answer.

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?

Front-loads the single governing rule ('pick the view by the question') before the view catalogue. The dense ·-separated list packs nine view semantics, their parameters, and three caveats into a few lines with no filler sentences.

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 an 11-parameter, read-only tool with no output schema, the description covers the required view enum, per-view parameter applicability, pagination, and even partial return hints (PRs, bests, next workout, resolution). What it omits — full return shapes and limits on 'sets' paging beyond the cursor — is minor given the annotation coverage.

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 coverage is 82%, so a baseline of 3 applies. The description goes beyond it by mapping parameters to views (muscle_group for muscle_state/muscle_group_progress, weeks for progress/status, exercise_name/exercise_ids for exercise_progress, include_all for recommendations) and clarifying 'omit for all', which the schema does not state as a cross-parameter rule.

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?

Opens with a specific verb+resource ('Training analysis') and immediately clarifies the core mechanic: the view parameter selects the analysis. The nine enumerated views make the scope unambiguous. It does not explicitly distinguish itself from siblings like read_workouts or exercises, which keeps it from a 5.

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?

Each view is paired with the question it answers ('strength_climb: am I getting stronger', 'insights: weekly review', 'status (weeks): adherence, next workout'), which is an effective routing guide. It also flags the partial_week caveat for week-to-date data. It stops short of naming when to prefer a sibling tool instead.

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