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

Annotations already declare the tool read-only and idempotent, and the description adds useful behavioral context: causal truncation with final/current-vintage inputs, and the expected result pattern that external wrecks transmit while crypto-native wrecks do not move the board. Terms like 'causal truncation' and 'current-vintage' are not unpacked, which keeps this from a 5.

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-load the subject, give concrete examples, state the interpretive behavior, and end with explicit usage guidance. Every sentence earns its place and there is no 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?

For a zero-parameter, read-only, idempotent tool with an output schema, the description sufficiently covers purpose, dataset contents, behavioral interpretation, and usage context. The output schema handles return-value details, so no further structured information 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 100% schema coverage, so the description carries no parameter-semantics burden. The zero-parameter baseline of 4 is appropriate; no unnecessary parameter details are introduced.

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 resource — labelled crypto stress episodes replayed against the dollar-funding board — and a concrete question it answers: whether TradFi funding stress reaches crypto. The named episodes and interpretive framing distinguish it from the broader sibling market-context 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?

It explicitly says 'Use for any ... question, grounded in the record,' which gives clear when-to-use guidance. It does not name alternatives or state when not to use it, so it stops short of full exclusion/alternative guidance.

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