setup_status

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

No annotations provided, so the description carries full burden. It details what is returned (API key state, data counts, profile, next_steps, capabilities, analyst_context) and includes critical behavioral rules like treating capabilities as a hard gate and not fabricating answers. This is thorough and transparent.

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 three sentences, front-loaded with purpose and usage, then lists return fields, and ends with a behavioral rule. Every sentence adds value without redundancy.

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?

Despite no output schema, the description fully explains the return values and usage rules. For a zero-parameter diagnostic tool, it provides all necessary context for an agent to invoke 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?

Input schema has zero parameters with 100% coverage, so baseline is 4. The description adds value by explaining the output structure, which compensates for the lack of an output schema.

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 clearly states 'One-shot setup diagnostic' and instructs to call at the start of every conversation, making the purpose obvious. It also implicitly distinguishes from sibling tools by being an initialization call, not a data operation.

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?

Explicitly states when to use: 'Call at start of every conversation, and any time the user asks for analysis but you're unsure what data is available.' Provides context for usage but does not explicitly list when not to use or alternatives, though the sibling list implies this is for initialization only.

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