Product Brain Snapshot

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

Annotations already mark this as read-only and idempotent, and the description adds valuable behavioral detail: it returns one JSON object, empty blocks when sources aren't flowing, newest-first customer signals, time-window honoring, and single-call/no-pagination behavior. This goes well beyond the annotation safety profile.

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 structured with a clear lead sentence, a colon-delimited list of return contents, and a final usage directive. It's slightly verbose with phrases like 'so YOU can reason about it,' but every major clause carries informational weight.

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 compensates by enumerating the exact JSON blocks returned and explaining empty-block behavior. It also covers parameter defaults, optionality, and how this tool relates to sibling reads, making it fully self-sufficient for selecting and invoking the 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 coverage is 100%, so baseline is 3, and the description adds extra context: product_id is 'from whoami' and the org's primary product when omitted, and the window parameter explicitly affects the time-windowed sections. This is useful but not dramatically beyond 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 this tool returns a single JSON snapshot of the org's product, listing the contained blocks (revenue, analytics, features, signals, open-work counts). It explicitly differentiates from siblings by saying 'Start here to ground, then go deeper with the dedicated list_* reads and the analytics tools.'

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 usage guidance: use this as the grounding entry point, then go deeper with list_* and analytics tools. It also clarifies that product_id is optional and defaults to the org's primary product, and that window choices are 7/30/90 days.

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