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

Annotations already declare readOnly, idempotent, and non-destructive. The description adds contextual value by stating it is 'Read-only public research data' and clarifies it involves no account access, order placement, or fund transfers, plus 'Not investment advice.' This goes beyond annotations, disclosing the data nature and usage limits.

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 concise and well-structured. It starts with a clear purpose, then details the key sections, then routes to alternatives, and ends with safety caveats. Every sentence contributes value, and the most important information (purpose and sections) is front-loaded. It could be slightly more organized, but it's 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?

Given the tool has 9 optional parameters and an output schema, the description is sufficiently complete. It covers the core purpose, the behavior of the sections parameter, and safety/usage constraints. The output schema covers return values, and the schema descriptions handle parameter details, so nothing critical is missing for an agent to select and 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 coverage is 100% with descriptions for every parameter, so the baseline is 3. The description adds extra meaning for the sections parameter, explaining what each section returns (issuance_flow gives CryptoQuant net issuance/redemption, usage_structure gives real usage metrics, depeg_events gives a de-peg event library). This provides semantic context beyond the schema's simple enumeration, justifying a 4.

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 resource (stablecoin) and action (ranking or per-symbol chain breakdown), clearly distinguishing it from generic market overview tools. It explicitly differentiates from siblings by naming get_market_overview and get_defi_overview as alternatives for broader scopes, so an agent knows when this tool is the right fit.

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 context for when to use this tool (stockson stablecoin-specific queries) and explicitly points to get_market_overview for broad market dashboards and get_defi_overview for cross-sector rollups. It does not state exclusions beyond those alternatives, but the guidance is sufficient to route the agent correctly.

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