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

With no annotations, the description carries the full burden of behavioral disclosure. It states what the call returns (full research, abbreviated metrics, AI analysis) which covers the primary behavioral effect. It does not claim any side effects, and the read-only nature is clearly implied. It does not mention rate limits or authentication, but for a research tool that is usually not necessary. The description adds sufficient transparency beyond the raw schema.

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 two tight sentences. The first sentence states the action and bound, the second enumerates the output. Every clause earns its place; there is zero fluff. It is also front-loaded with the core purpose before details.

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 read-only comparison tool with no output schema and no annotations, the description covers the key aspects: what input it takes (primary + comparisons) and what output it produces. It does not clarify whether token identifiers are addresses or symbols, but the schema also leaves that open, so the description is not uniquely deficient. Given the tool's simplicity, this is close to complete.

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 every parameter already has a description (e.g., 'Primary token to research', 'Tokens to compare against (1-3)', 'Blockchain network'). The tool description merely rephrases the primary/compare roles ('primary token', 'up to 3 others') and does not add new meaning beyond what the schema already provides. Thus the baseline score of 3 applies.

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 opens with a specific verb ('Compare') and a clear resource ('a primary token against up to 3 others'). It explicitly states the output mix (full research on primary, abbreviated metrics on comparisons, AI comparative analysis), which neatly distinguishes it from single-token siblings like token_research or token_intel. No ambiguity about what this tool does.

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 makes the use case obvious: use when you need a comparison across multiple tokens. However, it does not explicitly say 'for single-token deep dives use token_research' or otherwise state when NOT to use this tool. The context is clear but lacks explicit exclusions or alternative routing, so it misses the top bar.

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