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

Annotations already declare readOnlyHint=false, destructiveHint=false, openWorldHint=false, so the agent knows this is a non-destructive creation call. The description adds that the program is AI-generated from team workouts, hinting at a non-trivial generation step, but says nothing about latency, cost, idempotency, or whether the generated program is persisted or merely returned — meaningful gaps for an AI-generation operation.

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?

Two tight, front-loaded sentences with no filler — the purpose leads and the usage cue follows. It is efficient, though arguably undersized for a 13-parameter generative tool where a little more structure would have earned its place.

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?

An output schema exists, so return values needn't be described, but the tool's complexity (13 all-optional params, AI generation, enum constraints, age/gender/fitness-level targeting) is not reflected at all. An agent has no basis from the description for deciding which parameters matter or what a sensible call looks like.

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 13 parameters at 0% schema description coverage and zero required fields, the description carries the full documentation burden and provides almost none of it — no mention of team_id, goal_ids, week ranges, difficulty, end-user attributes, or user_requirements. The only hint is "multi-week," which loosely gestures at min_weeks/max_weeks. This is a serious gap for a tool the agent could easily call with wrong or incomplete 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?

States a specific verb and resource ("Generates an AI training program using team workouts") and scopes it to multi-week programs built from the user's existing workout library. However, it does not differentiate itself from the very similar sibling `create_program` (nor `generate_workout`), so an agent must infer which one produces an AI-generated vs. manually created program.

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?

"Use when the user wants to create a multi-week program from their workout library" gives implied usage context, which is better than nothing. But with `create_program`, `generate_workout`, `recommend_plans`, and `adapt_plan` all in the sibling set, the description offers no when-not guidance or alternative routing for the near-identical `create_program`.

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