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

The description adds a genuinely useful behavioral fact beyond the annotations: the call is paid and pricing lives in get_pricing. Annotations cover the rest of the profile (openWorld, non-idempotent, non-destructive), but the description says nothing about latency, rate limits, or how fresh 'fresh' is.

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?

Two tight clauses, cost caveat front-loaded and output fields enumerated without filler. Slightly dense but no sentence is wasted.

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 an output schema present, the description need not explain return values, yet it still names the score, catalyst and volume trend, and flags the paid model. The missing piece is routing guidance relative to the sentiment/brief siblings.

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 description coverage is 100%, so the schema already fully documents the single 'q' parameter with format and length. The description's 'any Polymarket or Kalshi market question' adds a mild domain constraint but no syntax or example beyond the schema. Baseline 3 applies.

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?

Names a specific verb/resource (fresh X sentiment) plus the concrete output shape (score -100..100, catalyst, volume trend), and scopes it to Polymarket/Kalshi market questions. It does not explicitly distinguish itself from the nearby get_sentiment_shift or get_market_brief siblings, so the agent must infer the split.

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 only usage signal is 'Paid (see get_pricing)', which tells the agent about cost but not when this tool is the right choice versus get_sentiment_shift or get_market_brief. No when-not-to-use or alternative routing is given.

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