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

Annotations already establish the tool as read-only, idempotent, and non-destructive. The description adds useful behavioral context beyond those annotations: cost ($0.05 US), exact output structure (probability, direction, 3-5 bullets, main risk), and the declared evidence sources (chokepoints, GDELT, fed watch, maritime, weather). No contradictions found.

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 a single dense sentence that packs purpose, input, output, source categories, target audience, and cost without excessive fluff. It is compact and front-loaded, though a touch more structure would improve scannability.

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 a single parameter and an output schema present, the description covers the essential usage details: what input to provide, what output to expect, and why an agent would use it. Minor gaps remain, such as how to format the market slug or what 'INDECISO' implies, but these are not critical for an agent to select and invoke 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?

The input schema only describes a generic 'input' string, which is low-information. The description compensates by specifying the meaningful parameter: a market slug. It also clarifies that input can be JSON or text, aligning with the schema. This adds real semantic value beyond the 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 what the tool returns: probability, direction (YES/NO/INDECISO), 3-5 evidence bullets with sources, and main risk for a Polymarket market slug. It is specific about the resource (prediction market) and the output, though it does not explicitly differentiate itself from siblings like market_resolution or polymarket_resolution_watch.

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 explicitly identifies the intended audience and use case: 'For agents deciding whether to bet or move assets.' This gives clear context for when to use the tool, though it does not mention when not to use it or compare it to alternative sibling tools.

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