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

With no annotations provided, the description carries the full behavioral disclosure burden and succeeds well. It discloses the data provenance, determinism, lack of LLM involvement, refusal behavior for unsupported markets, and the exact payment method and price. These traits go beyond anything the schema or annotations provide.

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 dense and front-loaded with the core purpose, and every clause contributes useful information about inputs, outputs, behavior, or cost. It is somewhat run-on as one long sentence, which hurts readability slightly, but there is no wasted or redundant content.

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 there is no output schema CPA and no annotations, the description compensates well by listing the output components: daily closes, fill counts, volume, open, high, low, last, 1-day and 1-week change, days to end date, and window volume. It also covers payment, refusal behavior, and determinism, so an agent has enough context to invoke the tool correctly.

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 baseline is 3. The description repeats what the schema already documents: market can be a slug, 0x condition id, or numeric id, and days is 1–365 with a 90 default. It does not add meaningful new parameter semantics beyond what the schema and name already convey.

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 leads with a specific, unambiguous statement: 'The daily YES-price history of one Polymarket market.' It names the exact resource (one market's price history) and the action (getting the historical series), and reinforces scope with 'History, not a prediction,' which helps differentiate it from prediction or screening 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?

The description gives clear practical context: it identifies the accepted market identifiers, the valid days range, default value, and the fact that unsupported markets are refused before payment. It does not explicitly name sibling tools or state when not to use them, but phrases like 'one Polymarket market' and 'History, not a prediction' imply the appropriate selection.

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