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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so safety is covered. The description adds meaningful return-shape context (the full manifest including source code) that no output schema supplies, though it says nothing about size/cost of fetching full source.

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?

Two sentences, zero filler, and the return contents are front-loaded before the call-ordering directive. Every sentence earns its place.

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?

With no output schema, the description carries the burden of describing return values and does so concretely (metadata, notes, revision history, dataset schemas, source). Combined with annotations covering the safety profile, 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 100%, so slug, revision, and include_source are already fully documented in the schema. The description's phrase 'in full' and mention of 'revision history' only loosely gesture at include_source/revision, adding little beyond what the schema provides; baseline 3 applies.

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 ('Returns') and resource ('one view in full') and enumerates exactly what comes back: metadata, notes, revision history, dataset schemas, and React source. It is clear what the tool does, though it does not explicitly distinguish itself from siblings like check_view or get_workspace.

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?

'Always call this before update_view so your edits match the current source exactly' gives an explicit trigger condition and names the alternative workflow it feeds into. An agent knows precisely when this tool is required rather than optional.

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