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

The description goes well beyond the annotations. It discloses that publishing is VERIFIED-LIVE (never reports a false positive), that it audits internal links, content contradictions, and JSON-LD/sitemap/robots coverage, that the audit comes back via get_publish_status as `report`, and that the call returns immediately while going live takes minutes. This is rich behavioral context that annotations (readOnlyHint=false, destructiveHint=true) do not provide. No contradiction with annotations.

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 dense but well-structured, front-loading the core purpose and then adding critical behavioral details and usage warnings. Every sentence earns its place, though it is longer than the typical description. The structure is logical: purpose, verification behavior, audit behavior, return behavior, and polling 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 complexity (verified-live publishing, audit, async behavior) and the presence of an output schema, the description covers everything an agent needs: what it does, what to expect, how to handle the async nature, and how to follow up. The output schema handles return values, so the description needn't explain them. No gaps.

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 100%, so the schema already documents both parameters (app_id and context). The description does not add parameter-specific meaning beyond what the schema provides, but it does add context about the overall operation. Baseline 3 is appropriate.

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 states a specific verb ('take a website LIVE at its public URL') and clearly distinguishes this from siblings like get_publish_status (which reports status) and check_domain/connect_domain (domain setup). It also names the sibling get_publish_status explicitly, making the tool's role unambiguous.

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 gives explicit when-to-use guidance ('Use this to take a website LIVE'), and also provides a clear when-not-to-use: do NOT poll get_publish_status in a loop; instead tell the user it is publishing and check once when they ask again. It also instructs to read the audit report from get_publish_status before telling the user the launch went well. This is exemplary usage guidance.

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