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

Annotations only cover safety/idempotency, and the description goes well beyond them: it discloses that the view is compiled, test-rendered in a real browser and reviewed immediately, that the response reports render status/errors/gaps, that a thin brief is refused once, and that two outside services (TypeSafe, OpenAI) process the brief and a screenshot. That external-service data exposure is exactly the kind of context annotations cannot carry.

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?

Purpose and constraints are front-loaded and nearly every sentence carries operational content. It is long (~10 sentences) and some material (the brief, the questions ordering) duplicates the schema's own descriptions, which slightly dilutes conciseness.

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 12-parameter tool with nested objects and no output schema, the description covers what is missing from structured data: the data-binding contract for `source`, the refusal behavior, and what the response returns. An agent has everything needed to call it correctly.

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 already 100%, so the schema carries the parameter definitions and a baseline of 3 applies. The description still adds real meaning: `source` must be ONE file of React that default-exports a component and reads data via useDataset from 'quillm', and `questions` must be written before the source. It does not, however, add much for the many other required fields.

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 ('Creates a new view') and immediately defines what a view is: 'a live page at a stable URL in the user's dashboard app.' It explicitly distinguishes itself from siblings create_dataset and update_view, so an agent can select it without opening any 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 explicit sequencing and alternatives: create the dataset first via create_dataset, call get_guide first for the template, check get_workspace first and use update_view if a suitable view already exists. When-not-to-use (existing view) and prerequisites are all spelled out.

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