log_set

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

With no annotations, the description carries the full burden of behavioral disclosure. It documents side effects (starting a workout if none is open), state reuse (last exercise/unit), defaults (bodyweight, unit), and return behavior (logged sets, PRs, and the workout-end card).

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 compact and front-loaded with the primary purpose, followed by terse parameter guidance. Every sentence adds useful information, and the concrete examples make behavior concrete without padding.

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 nine parameters, no output schema, and no annotations, the description covers the core workflow, parameter semantics, defaults, return values, and special text behavior. An agent has enough context to invoke this tool correctly in most conversational scenarios.

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. It adds meaning for exercise, weight, unit, kind, count, and text, including concrete examples and defaults. It does not explicitly explain reps, rpe, or notes, though reps and notes are reasonably self-evident.

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 specific verb and resource: "Log a set to the current workout," and adds an important scoping behavior ("starting one if none is open"). This clearly distinguishes it from siblings like edit_last_set, end_session, and log_food.

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 clearly establishes the context for use: logging a set in the current workout, with special handling for raw text input and workout-ending messages. It does not explicitly name alternative tools or exclusion criteria, but the intended use case is unambiguous.

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