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

Beyond the readOnly/openWorld annotations, it discloses pricing ($0.6 USDC via x402 across four chains), the payment flow and automatic-pay clients, the minimum-source error behavior with a no-charge guarantee, and that citations plus a source list are returned. This is exactly the cost/auth/failure context annotations cannot carry.

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?

It front-loads what the tool produces before diving into pricing and the sample call, and the enumerated constraints (kind, language, error rule, price) each carry information. It is dense, verging on crammed, but no sentence is redundant for a paid open-world tool.

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 7-parameter, no-output-schema tool with annotations, it covers return format, length, sourcing, payment and failure semantics. It does not spell out pagination or the exact citation/source-list shape, but that is minor given the overall coverage.

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 already 86%, so the baseline is 3, and the description adds real value on top: kind defaults to topic, language is en or de, and length long doubles the word budget (1200-1800 vs 500-900). chain and token are only lightly framed, but the effective-schema work is done.

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?

It names a specific deliverable (AI-written Markdown report), its scope (topic, company or token), its length envelope, and its source bases, so the agent knows exactly what comes back. It is clearly distinguishable from adjacent siblings like company_brief, answer_with_sources and page_summarize because of the cited-report framing.

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?

"Use for due diligence and briefings" gives a concrete usage context, and the kind values are tied to input modes. It stops short of naming when-not-to-use or routing to alternative tools (company_brief, news_search, answer_with_sources), so it is clear context without exclusions.

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