kernel_today_card

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

With no annotations supplied, the description carries the full disclosure burden and does well: it names the three output representations (text, structured JSON, HTML 'ui' block) and explains the client-dependent rendering fallback to markdown. It omits operational traits such as permission requirements, cost/latency, or whether the aggregate is cached or live.

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?

Three sentences, front-loaded with the core purpose, followed by the aggregate contents and then the rendering behavior. Every sentence adds information and none restates the title or name.

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?

An output schema exists, so the description is not obligated to explain return values, and it still usefully characterizes the aggregate scope and multi-format delivery. The only meaningful omission is any explanation of the 'accent' parameter, which leaves one structured field unexplained end to end.

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?

The single parameter 'accent' has zero schema description coverage and is never mentioned in the description, so no meaning is added beyond the enum values themselves. The gap is low-risk because the parameter is cosmetic and its enum is self-explanatory, but the description does nothing to compensate for the coverage hole.

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 and resource — 'one-call snapshot of your day' — and enumerates exactly what is aggregated (events, tasks, drafts, trades, session PnL). An agent knows precisely what this returns. It does not, however, differentiate itself from the similar-sounding sibling kernel_meta_render_card, which also deals with cards.

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?

It gives a concrete trigger condition: use it when the agent or human asks 'what does today look like'. That is a clear usage context. There are no exclusions or named alternatives for cases where a narrower tool (e.g. a tasks-only or events-only query) would be preferable.

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