get_workout_snapshot

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

With no annotations provided, the description carries the full burden, and it does substantial work: it discloses that the token is versioned by MCP rather than an upstream ETag, that missing fields/null/zero remain distinct, that pairing evidence is read by exact identity, and that the read does not authorize a write. It also flags unverified aspects (source completeness, atomic conditional writes). This is rich behavioral disclosure beyond a simple 'read' label.

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 first sentence is a strong front-loaded summary, but the rest is a dense paragraph of caveats and domain-specific rules. Every sentence carries information, but the structure is heavy and could be broken into clearer sections. It is not bloated, yet it is harder to parse than necessary for an agent.

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 and the presence of an output schema, the description covers the critical behavioral context: versioning semantics, pairing checks, precondition safety, and write authorization limits. It does not explain the return structure, but the output schema exists and the description need not duplicate it. The main gap is parameter semantics for api_key and athlete_id, but overall the agent has enough to invoke the tool correctly.

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 0%, so the description must compensate for the three parameters. It explains the central role of event_id (the event whose snapshot is read) and mentions event-by-ID and calendar-day logic, but it does not explicitly define api_key or athlete_id or explain when they are needed. The description adds meaning for the main parameter but leaves the optional parameters under-specified.

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 a clear verb and resource: 'Read a workout's raw event, server version and execution precondition.' This distinguishes it from sibling getters like get_activity_details or get_events by focusing on the snapshot/versioning purpose. However, it does not explicitly name a sibling alternative, and the dense follow-up text makes the core purpose slightly harder to isolate.

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 gives strong usage context: it explains when this read is appropriate (binding data.event_fingerprint in an execute_operation precondition) and when it is not ('This read does not authorize a write'). It also warns that unpaired_observed does not prove the athlete did not train. It does not explicitly name alternative tools, but the context is clear enough for an agent to decide when to call it.

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