justhandled_channel_fit_evidence_matrix

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

With no annotations, the description carries full responsibility for disclosing side effects and operational behavior. It does mention the $0.25 USDC cost on Base mainnet, which is useful, but it fails to state whether the tool is read-only, what it returns, whether it persists data, or what happens on failure. This is insufficient for a tool with financial cost.

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 a single, front-loaded sentence that begins with the verb and resource, lists the key dimensions, and ends with the cost. It contains no filler or repetition, and every element adds necessary information.

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 highly complex nested schema, no output schema, and no annotations, this description is incomplete. It explains the ranking purpose and cost but omits how to assemble the evidence and constraints inputs, what the output looks like, and any operational requirements. For a tool with 100-item and 500-item arrays, more contextual guidance is essential.

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 description coverage is 0%, so the description must compensate for the complex 5-parameter input. The long list of ranking criteria maps to nested channel fields (audience_match, buyer_intent, etc.) and adds some meaning, but it does not explain the required top-level parameters like observed_at, objective, constraints, evidence, or channels. The description only partially clarifies the input structure.

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 starts with the specific verb 'Rank' and clearly identifies the resource as 'evidence-backed distribution tests' with a detailed list of ranking criteria. This makes its purpose distinct from sibling tools like proof_to_channel_evidence_packet or qualified_demand_ledger, which focus on evidence construction or ledgering rather than comparative ranking.

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 offers no explicit guidance on when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. Usage is only implied by the action word 'Rank', so an agent must infer the appropriate context without support.

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