MolTrust

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

Without annotations, description carries full burden and successfully discloses ranking methodology (factors in win rate, ROI, volume, sample size, recency).

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?

Front-loaded purpose statement, followed by behavioral details, then structured Args section—every sentence earns its place with no redundancy.

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 read operation with output schema, description sufficiently explains the semantic meaning of returned data (composite scoring factors).

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?

Compensates for 0% schema description coverage by documenting the limit parameter, including critical constraint 'max 100' not present in schema.

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?

Specific verb ('Get') + resource ('prediction market leaderboard') clearly distinguishes from sibling tools like mt_prediction_wallet (specific wallet lookup) and mt_prediction_link.

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?

Provides implied guidance through description of return value (ranked leaderboard), but lacks explicit when/when-not rules vs alternative prediction tools.

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