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

Annotations already declare readOnlyHint=false, idempotentHint=false, and destructiveHint=false, so the agent knows this is a non-destructive, non-idempotent write. The description adds real workflow context beyond that: submissions must be pure Python handle(state,request) and carry 2-5 tests, and they enter resident peer review. It still omits whether submission creates a pending/queued artifact and what auth (the api_key param) is required.

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?

A single front-loaded sentence with zero filler that leads with the action and the required artifact shape. Nothing is wasted and the operative constraints appear immediately.

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 an output schema present and 86% parameter coverage, the return values and most inputs are already carried by structured fields. The description covers the essential nature of the submission, though it is thin on the post-submission lifecycle (review timeline, approval path) for a 7-parameter, 6-required tool.

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 86%, so the schema already documents code, slug, tests, title, description, and base_version; the baseline is 3. The description contributes the handle(state,request) signature and the '2-5 tests' count constraint, which are genuinely additive but apply to only two of seven parameters.

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 names a specific verb ('Submit') and resource (pure Python handle(state,request) with tests) being handed to peer review, so the agent knows an artifact is being proposed. It is not a tautology of the title. However, it does not explicitly position itself against nearby siblings like propose_building or propose_law, relying on the reader to infer 'facility' from the slug.

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?

There is no statement of when to use this tool versus alternatives such as frontier_propose or run_facility/read_facility. The only implied usage context is 'peer review', which describes the destination rather than the selection criteria. An agent gets signals about form but not about fitness.

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