add_state_machine_state

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

With no annotations, the description carries full burden of behavioral disclosure. It only states the action without mentioning side effects, prerequisites, error behavior, or whether the operation is reversible. For a mutating tool, essential context is missing.

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 a single clear sentence that efficiently conveys the core action without unnecessary words. It is concise and well organized.

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?

With 7 parameters, no annotations, and no output schema, the description is insufficiently detailed. It lacks parameter explanations, behavioral constraints, and usage prerequisites, making it difficult for an agent to invoke the tool correctly in varied 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 for unexplained parameters. It provides some context for state_type (animation, blend tree, nested state machine) and position (graph position), but node_path, state_name, animation, and state_machine_path are not explained beyond their names, leaving key semantics ambiguous.

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 adds a state (animation, blend tree, or nested state machine) to an AnimationTree state machine at a graph position. This distinguishes it from sibling tools like add_state_machine_transition and remove_state_machine_state.

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?

Usage is implied through context: it is for adding states to an AnimationTree state machine, but there is no explicit when-to-use or alternatives guidance. The description does not mention when to use this vs other state machine tools.

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