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

Annotations already declare readOnly, idempotent, open-world, non-destructive behavior, so the description isn't burdened with the safety profile. It adds genuinely new context: results carry a confidence score, and each call costs $0.05 USDC via x402 — important pre-invocation cost information the annotations do not convey. It doesn't say what happens when no handle is found, keeping it below 5.

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?

Purpose, use cases, output shape, and cost are delivered in three front-loaded clauses with no filler. Nothing in the text is redundant with the name or 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 lookup with no output schema, the description covers purpose, entity scope, confidence score, language support pricing, and the payment model — enough to call it correctly. Only the no-match/failure behavior is left unstated.

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 both parameters are documented (including the language enum), so the baseline is 3. The description adds value by showing the lookup accepts loose descriptive phrases like 'sf 49ers' rather than requiring exact names, which is semantics beyond the schema's 'Amazon CEO' example.

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?

States a specific verb and resource ('X (Twitter) handle lookup: finds the X handle') plus the range of entity types it accepts, which cleanly separates it from siblings like interzoid_x_profile and interzoid_x_last_three_posts. The parenthetical example ('sf 49ers' to @49ers) makes the input-to-output mapping concrete.

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?

Gives named use cases (social media enrichment, influencer and brand research, contact enrichment) that tell the agent when this tool fits. It does not explicitly exclude alternatives such as interzoid_x_profile or interzoid_x_last_three_posts or state when not to use it, so it stops short of a 5.

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