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

Annotations already declare readOnlyHint=true, so the description doesn't need to restate safety. It adds valuable behavioral context: the include_data_quality=true option triggers an extra set-history scan and yields a data_quality block, and it explains what that block contains (e1RM coverage, fragmented variants, etc.). This goes beyond the annotation and helps the agent anticipate cost and output shape.

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 front-loaded with the core purpose, then usage guidance, then the parameter explanation. It is a bit long but each sentence earns its place—no filler. The sibling routing is compact and helpful.

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 orientation snapshot tool, the description covers all essentials: what it returns, how to use it, the optional parameter and its cost/benefit, and how it differs from related tools. The output schema exists, so return-format details need not be spelled out. Nothing critical is missing for a correct first call.

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 schema already describes include_data_quality as 'Also compute and attach the data_quality block (adds one set-history scan).' The description enhances this by listing the exact contents of the block and framing it as 'the coverage context that tells you which numbers the data actually supports.' This adds practical meaning beyond the schema's terse note.

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 clearly states the tool returns a 'compact overview' of the user's training setup and recent activity, enumerating specific contents (profile, routine, next workout, last 10 summaries, records). It also distinguishes itself from siblings like get_training_insights and get_training_status, so an agent can tell them apart without opening schemas.

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?

Explicitly instructs to 'Use this as a first call to orient yourself on who the user is and what they're doing.' It also names alternatives for specific needs: deeper analysis via get_training_insights, adherence via get_training_status, full per-exercise list via list_trained_exercises. This gives clear when-to-use and when-not-to-use guidance.

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