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

Annotations only cover readOnly/openWorld, so the description carries the real behavioral load and delivers: 40-120s runtime, async job semantics with webhook support, a no-charge condition when too few sources are found, the async pre-check ordering, and a $3 USDC x402 cost. Billing, latency, and failure-refund behavior are exactly the traits an agent cannot get from structured fields.

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?

Front-loaded with the deliverable, then constraints, then billing; no filler sentences. It is dense to the point of being crammed with parentheticals (async caveat, pricing), which slightly hurts scannability but every clause carries 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?

With no output schema, the description appropriately describes the return (per-competitor profiles, comparison narrative, differentiation opportunities, PDF). It also covers the timeout and no-charge edge cases. The remaining gap is target identification (name vs domain) and what happens on failed async jobs beyond the refund rule.

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 67% and the description mostly restates it (count 3-8, pdf, async), adding only modest meaning. Critically, with 0 required parameters it never explains how to identify the target — whether to pass `name`, `domain`, or both — which is the single most decision-relevant ambiguity for this call.

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?

Names a specific deliverable (competitor landscape for a company/product) and enumerates the pipeline: web discovery of direct competitors, website/tech-stack profiling, model-driven comparison of positioning, target customer, strengths, weaknesses, threat level, plus differentiation opportunities. This is clearly distinguishable from siblings like report_company, report_market, and techstack without opening any schema.

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?

Usage context is implied by the 3-8 competitor scope, the 40-120s latency, and the async flag, but no alternative tool is named and no explicit when-not-to-use condition is given (e.g. report_company vs report_market vs this). The agent must infer routing from the sibling list alone.

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