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

Adds meaningful behavior beyond the annotations: it consumes inference credit (cost), lands on the Studies page in draft state, and may return a `needs_confirmation` signal. The annotations only cover the safety profile (not read-only, not destructive, closed-world), so these operational details are genuine added value, though the consequence of `needs_confirmation` is not explained.

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?

Front-loads the core action and scope in the first clause, then layers destination, cost, and confirmation behavior. The em-dash aside is dense but the whole block is efficient with no filler sentences.

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 credit-consuming mutation with no output schema, it covers where the artifact appears, how it's published, and the confirmation edge case. The missing piece is the relationship between the `needs_confirmation` return and the undocumented `approvalId` parameter, which would help an agent complete the flow.

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 coverage is 67% — `about` and `workspace` are documented in the schema, and 'anything you can describe in a sentence' loosely reinforces the free-form `about` input. The description adds no syntax or format detail beyond the schema and leaves `approvalId` unexplained, so the baseline 3 fits.

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?

States a specific verb and resource ('Generates and creates a DRAFT study') and immediately scopes it with the distinguishing trait 'isn't tied to any canvas node'. This lets an agent separate it from canvas-attached study drafting siblings without opening a schema.

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?

Gives concrete use cases ('brand tracking, workspace-level research, anything you can describe in a sentence') and points to prism_studies_update for publishing. It doesn't explicitly name the alternative (prism_studies_draft) or state when NOT to use it, but the scope line makes the choice inferable.

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