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

With no annotations provided, the description carries the full burden of behavioral disclosure. It fully discloses the reference-price basis, slippage-only scope, the deliberate exclusion of revert rates and MEV exposure, and the chain-blending caveat. These are meaningful behavioral traits that go far beyond what a generic tool description would include.

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 front-loaded with the core purpose, and each subsequent sentence earns its place by providing necessary caveats. It is appropriately sized for the tool's complexity, with no filler or redundant restatement of the input schema.

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 two-parameter read-oriented ranking tool, the description covers the metric, the scale, the caveats, the chain behavior, and the relationship to the sibling tool. Although there is no output schema, the description explains enough about the score to let the agent interpret results correctly; nothing essential is missing.

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%, so the baseline is 3. The description adds contextual meaning for the chain parameter (single-chain vs cross-chain rollup semantics) and reinforces the limit parameter's rationale regarding context-window constraints)Skip; the schema already documents clamping and range, but the description's caveats add interpretive value beyond raw parameter names.

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 verb ('Rank') and resource ('DEXs and aggregators'), defines the exact metric (median slippage against a minute-level off-chain reference price), and disambiguates itself from the sibling revert_rates by explicitly separating slippage from revert/MEV metrics. An agent can tell exactly what this tool produces and what it does not.

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?

Explicitly instructs the agent when to use the tool, what it must not do (present as 'best execution'), and directs the caller to ask revert_rates for the complementary data. It also gives clear chain-selection guidance ('pass a chain' vs 'all') and warns against misrepresenting the blended rollup. This is exemplary usage routing.

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