recover_gazebo_joints

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

With no annotations, the description fully discloses the operational sequence: resolving the model, requiring identity match, enforcing soft limits, stopping the controller, calling set_model_configuration, and verifying via get_joint_properties. It also transparently states that timed-out writes are ambiguous and that no CLI fallback or retry is attempted, which is critical behavioral information.

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 structured with a clear lead sentence, followed by a compact sequence of actions and a focused note on timeout semantics. It is slightly verbose but every sentence provides useful detail, and the front-loaded purpose makes it easy to scan.

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?

The tool has moderate complexity (four parameters, nested objects, output schema). The description covers the operational workflow and edge-case behavior well, but it omits parameter semantics for confirm_token and model_name and does not mention prerequisites like Gazebo being active. Given the output schema exists, return values are handled, but the incomplete parameter guidance prevents a higher score.

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 explain parameters. It explicitly explains timeout_sec, but model_name, confirm_token, and joint_positions are only indirectly referenced (e.g., 'resolves the live model' and 'rejects positions outside soft limits'). No explanation is given for confirm_token or how model_name is resolved, leaving significant semantic gaps.

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 'Safely recover simulation gimbal joints through Gazebo services', giving a specific verb (recover), resource (simulation gimbal joints), and method (Gazebo services). The phrase 'Simulation only' clearly distinguishes this from real-robot tools, and the detailed sequence further clarifies its role among siblings.

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 implies usage for safely recovering gimbal joints in simulation but does not explicitly state when to use this tool versus alternatives like get_joint_limits or configure_target. It gives context ('Simulation only') but lacks direct comparisons or exclusions, so it only meets the implied usage level.

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