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

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds valuable behavioral detail: it states the output is a top-level array, clarifies that the probability signal is in `outcomes` paired with `outcomePrices` and quoted against `bestBid`/`bestAsk`, and identifies `conditionId`/`clobTokenIds` for joining to other data. This goes well beyond the structured hints.

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 exactly three well-focused paragraphs: purpose with inline filter enumeration, return-shape explanation, and sibling routing. Every sentence adds information. No filler or repetition of the title, and the most important usage guidance (when to use) is front-loaded in the first sentence.

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?

Given 17 parameters, an output schema, and strong annotations, the description fully covers the tool's purpose, return-shape semantics, parameter categories, and sibling alternatives. An agent can decide to call this tool, know what it returns, and join the results to other Polymarket data without needing to open another schema.

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 coverage is 100%, and the schema already provides per-parameter descriptions and examples. The description adds semantic grouping beyond that: it names the exact filter parameters for market size and timing ('slug', 'condition_ids', 'clob_token_ids', 'tag_id', 'closed', and the volume/date ranges) and explains that some in-schema fields are on-chain identifiers for joining. It does not re-describe every parameter but meaningfully aggregates them for output.

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 states a specific verb and resource: 'List individual Polymarket prediction markets — one binary question each — with live pricing.' It immediately distinguishes itself by calling out the use case—market-implied probability of a specific outcome or screening by size and timing—and explicitly differentiates from siblings get_polymarket_events and get_kalshi_markets.

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 says when to use this tool: 'Use this when you need the market-implied probability of a specific outcome, or to screen markets by size and timing.' It also gives direct when-not guidance by routing users to get_polymarket_events for grouped topics and get_kalshi_markets for the US-regulated exchange. It names alternatives with clear criteria.

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