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

With no annotations present, the description carries the full disclosure burden and does well: it reveals the fail-closed read semantics, the 'unmeasured is never zero' convention, and that a section with nothing defensible returns empty rows plus a dataNote. It implies read-only behavior via 'fail-closed read models' but does not state permissions or rate limits — minor gaps for a read-only aggregation tool.

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?

Every sentence earns its place: purpose and content are front-loaded first, behavioral disclosure second, and usage guidance last. The prose is dense yet not wasted, packing scope, calculation source, empty-result behavior, and invocation timing into three purposeful sentences.

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?

For a 0-parameter tool with no output schema and no annotations, this definition is complete. It specifies the data sources (same models as the terminal), the three content sections, the empty-result dataNote behavior, the compact JSON format, and the invocation timing. Nothing an agent needs to call it correctly is missing.

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 tool has zero parameters and the schema coverage is 100%, so the baseline is 4. The description compensates for the missing output schema by detailing exactly what the returned data contains across its three sections, which is the closest analog to parameter/return semantics for a parameterless tool.

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 names a specific purpose — an aggregated 'one-call daily read' — and enumerates its exact contents: premium dislocations (with live-print vs frozen-oracle distinction), the forward corporate-action calendar, and Chainlink feeds that are not OK. This positions it as an aggregate digest distinct from granular siblings like chainlink_feed and pending_corporate_actions, making its scope 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?

Explicit guidance is given: 'Call this first each session, and before any batch of trades placed via a trading MCP server.' This gives a clear and actionable when-to-use instruction. It does not name alternatives or state when not to use it, but the 'first-call' framing implicitly differentiates it from the granular siblings.

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