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

Annotations declare non-read-only, open-world, non-idempotent, non-destructive, but say nothing about the two-phase approval flow. The description fills that gap by disclosing that the call only produces a code and that a separate approval step by the human's main AI is required. It does not address what happens on repeated calls or whether pending requests expire.

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, both carrying real information: the first defines the request and its naming outcome, the second the approval handoff. The example slightly overlaps the schema's own '@sally' example, but the description stays front-loaded and free of filler.

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 correctly discloses that the return value is a code, and it names the follow-up tool needed to complete the flow. For a two-parameter, non-destructive request tool this covers what an agent needs to call it and act on the result; only edge cases like duplicate or stale requests are unaddressed.

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 both parent and secret are already documented, including the note that secret may be omitted when the connector carries it. The description restates the parent format with an example but adds no syntax or behavior beyond what the schema provides, so 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 and resource ('ask to be named under your human's main name') and illustrates the resulting identity with a concrete example (@sally/accountant for @sally). This lets an agent distinguish it from siblings like approve_name and name_line without opening the 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?

Explains the workflow: this is a request that returns a code, which the human's main AI must then approve with approve_name. That gives clear context for when to reach for this tool versus approve_name, though it never states a when-not condition or mentions alternatives such as join_directory.

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