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

With no annotations, the description carries the full burden and does well: it declares the tool is a read ('Facts only'), explicitly disclaims investment advice/pricing/signal, discloses the $0.02 cost and credit mechanism, and notes that failed or empty calls are free. It does not mention rate limits or output formatting, but the coverage is strong for a read-only 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?

The description is four sentences, each earning its place: core output, disclaimer, cost/payment, and failure policy. It is front-loaded with the purpose and avoids fluff. Slightly dense with pricing and credit details, but every sentence carries operational value, so it remains efficient.

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 single-parameter tool with no output schema and no annotations, the description adequately covers what is returned, the cost, the failure behavior, and the nature of the output. It does not specify the exact output format or how 'cross-platform gap' is expressed (e.g., percentage points), but an agent has enough to call it correctly and interpret the result.

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%, and the schema already provides an example for q ('will the fed cut rates in september'). The description reiterates 'one question' but adds no new semantic detail about the parameter (format, constraints, or normalization). Baseline 3 applies because the schema does the heavy lifting and the description adds marginal value.

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 opens with a specific resource ('Prediction market odds') and a precise scope ('a finished read for one question'), and enumerates the delivered outputs: best-matching market on Polymarket and Kalshi, implied probability, cross-platform gap, 7-day history, and a one-line summary. It implies differentiation from siblings like pm_search or pm_ticker_events through 'finished read', but does not name an alternative, so it stops short of a 5.

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?

Clear context is established: this is for a single question and returns a complete snapshot, which tells an agent when to reach for it. It also states the prerequisite of obtaining a key via buy_credits and the pricing model. However, it gives no explicit exclusions or alternatives (e.g., 'use pm_search instead for raw market lists'), lowering it below a 5.

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