apply_ai_onboarding

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

With no annotations provided, the description carries the full behavioral burden but discloses almost nothing: no mutation semantics, side effects, permissions, idempotency, or failure behavior. The single useful detail is the requirement that geometry_repairs mode match the later conversion, but that is insufficient for a tool whose name implies applying onboarding.

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 short and front-loaded, but its two clauses are cryptic rather than informative. It avoids verbosity, yet the main clause does not clearly orient the reader before introducing the geometry_repairs constraint.

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 five-parameter tool with a nested proposal object, no annotations, and 0% schema description coverage, the description is drastically incomplete. Even though an output schema exists, the input behavior and required setup are almost entirely undisclosed.

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 five undocumented parameters. It hints that source and proposal are related via "source-bound proposal" and mentions geometry_repairs mode, but project_dir, proposer, the proposal object structure, and source format are left entirely unexplained.

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 says "Compile a source-bound proposal" but does not explain what applying AI onboarding means or how this differs from sibling tools such as prepare_ai_onboarding, auto_onboard_and_convert, or run_conversion. The verb "compile" is specific, but the resource and effect on the project remain vague.

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 only guidance is the constraint that conversion must use the same geometry_repairs mode. There is no statement of when to use this tool instead of prepare_ai_onboarding or auto_onboard_and_convert, no prerequisites, and no exclusions.

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