make_pivot

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

With no annotations provided, the description carries full burden for behavioral disclosure. It fails to state side effects (e.g., creating a file in the project), whether the operation is read-only or destructive, auth requirements, or what happens if the table name is invalid or already exists. The brief description leaves significant behavioral gaps, which is problematic for a tool that creates files.

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 concise (two sentences) and front-loaded with the primary action. Each sentence adds value: the first states the core purpose, the second provides implementation detail. It is efficient without unnecessary words, though it could be more structured (e.g., separate usage guidance).

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 the tool's simplicity (1 parameter, no output schema, no nested objects), the description is somewhat complete for purpose. However, it lacks essential details for usable execution, such as side effects (file creation), required dependencies (e.g., existing D1 connection), and error behavior. The sibling tools include many scaffolding and migration tools, and the description does not address how pivot differs from make_migration or when to prefer this over manual methods.

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?

The input schema has 1 parameter with 100% description coverage ('Pivot table name'), so the schema itself documents the parameter. The description adds no supplementary meaning beyond 'Pivot table name', but the high coverage means the schema suffices. Baseline of 3 is appropriate; the score is 4 because the description's clarity reinforces the parameter's role (e.g., the 'table' parameter is the pivot table name, consistent with the description's focus on 'pivot table migration'). However, it could add format or naming conventions.

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 creates a pivot table migration ('Scaffold a pivot table migration'), using a specific verb and resource. While it distinguishes the tool's purpose from siblings like make_migration, it does not explicitly differentiate from other scaffold tools in the sibling list, such as make_model or make_factory, but the specific 'pivot' focus and reference to the underlying command provide good clarity.

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 lacks any guidance on when to use this tool versus alternatives like make_migration or other scaffolding tools. It does not mention prerequisites (e.g., needing a related model or migration context), exclude cases (e.g., skip if table already exists), or provide context for decision-making. The implied usage is simply to create a pivot migration, but without explicit guidelines, the agent may misuse it.

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