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

The description discloses that the tool edits the project and commits the result, which aligns with destructiveHint=true and readOnlyHint=false. It adds valuable unannotated behavior: turns can take minutes, after ~40 seconds a job_id is returned, and the work continues asynchronously.

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?

Three sentences with no filler: the first gives the core action, the second gives usage examples, and the third explains timing, return behavior, and the async path. The most important scoping detail is front-loaded.

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 a long-running agent tool with two schema-documented parameters and an output schema, this description covers selection, invocation, expected returns, and the asynchronous job_id behavior. An agent has enough context to call it correctly and to know what to do when it takes longer than expected.

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?

Both parameters are fully described in the input schema, so the description does not need to add much. The phrase 'described in plain words' lightly reinforces the message parameter, but no additional parameter-level semantics are provided beyond what the schema already covers.

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 states a clear action ('Send a task to Aurora's AI agent') and resource ('the project'), then gives concrete use cases: build a feature, change a design, or add an npm package. It also distinguishes itself from the chat_status sibling by explaining the job_id flow.

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 explicitly says when to use the tool ('Use this to have Aurora build a feature...') and mentions the chat_status fallback for long-running turns. It does not explicitly list when-not-to-use scenarios or compare against other siblings like apply_changes, but the intended context is clear.

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