Server Quality Checklist

Tool Scores

• get_marketA
  4.2/5.0
  Behavior4/5

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

  With no annotations, the description carries the full burden, and it delivers a genuinely non-obvious behavioral trait: lookups resolve through a precomputed cache and fall back to a direct Gamma lookup for ids outside the top markets by volume. It also previews return contents. It stops short of covering error behavior for unknown ids or latency differences between the two paths, but the most important behavioral disclosure is present.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Two sentences with zero filler. The main purpose is front-loaded in the first sentence, and the fallback nuance earns the second. The jargon ('precomputed cache's top markets by volume', 'direct Gamma lookup') is dense but conveys precise information efficiently.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a one-parameter tool with no output schema and no annotations, the description covers the essentials: purpose, expected return contents, and the one notable behavioral twist. The main gap is failure behavior — what happens when a market id is unknown even after the Gamma fallback — which is not addressed.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, so the description must compensate. 'By id' ties the sole parameter to the concept of a Polymarket market identifier, adding domain meaning the schema ('string', 'minLength 1') lacks. It doesn't specify id format or how to obtain one, but for a single parameter whose name is already self-explanatory, the compensation is adequate.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description states a specific verb ('look up'), a specific resource (a Polymarket market by id), and the returned content (details, live price, orderbook snapshot). The market-data domain clearly separates it from the sibling check_news without needing an explicit comparison.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  Usage is implied: when an agent has a market id and wants market details, this is the tool. However, there is no explicit when-to-use/when-not-to-use statement, no named alternative, and the fallback sentence describes internal resolution behavior rather than guiding tool selection relative to check_news.

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

• check_newsA
  4.4/5.0
  Behavior4/5

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

  With no annotations, the description carries the full behavioral burden. It discloses that the probability comes from a precomputed cache on a cron cadence and may be up to ~2 hours stale, and it explicitly says the tool does not classify whether news is dramatized. These are non-obvious behaviors an agent must know. It could add error behavior for unmatched news, but the key operational traits are transparent.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Two focused sentences: the first states the core function, and the second adds necessary limitations and the routing alternative. Every sentence contributes value, and the key behavior is front-loaded. No filler or repetition.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a simple one-parameter tool with no output schema, the description covers the main return values (YES probability and marketId), the data freshness caveat, and the alternative for live prices. It does not specify the exact response structure or behavior when no relevant market is found, but the essentials for correct invocation are present.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, so the description must compensate. It does by clarifying that 'text' is a piece of news text used as the input for market mapping. This adds meaningful semantic context beyond the raw schema constraints of minLength and maxLength. Still, it could be more explicit about input shape expectations, but for a single free-text parameter it is adequate.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description opens with a specific verb and resource: 'Map a piece of news text to the relevant Polymarket market and return its objective YES probability.' It clearly distinguishes this tool from get_market by stating that the returned probability is an objective market anchor backed by news text, not a live price.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description gives explicit context: this tool maps news to a market and returns a cached probability. It names the alternative get_market for live pricing before trading, which is a clear conditional routing. However, it does not explicitly state scenarios where check_news should not be used beyond the live-price case.

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