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

With no annotations, the description carries full responsibility for behavioral disclosure. It transparently notes that it uses only 'attested facts,' that sources are keyless, and that the tool 'returns the payment challenge unless already settled,' which is an important side effect. It does not describe error behavior or data freshness, but the key behavioral traits are disclosed.

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 paragraph that conveys the core functionality, sources, and payment model. However, it includes redundant pricing statements ('Keyless public sources; $2.00 (moat product #2). Price: 2.0 USDC per call') and repeats 'attested' twice. It could be tightened without losing meaning, but it remains readable.

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 no output schema, the description adequately explains what the tool returns (a machine-formatted DD brief built from attested facts) and mentions the payment challenge. It also lists the input filters and source domains. While it could specify the exact output format or response structure, the provided context is sufficient for basic invocation and expectation-setting.

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 descriptions already cover all six parameters (drug, focus, nct_id, sponsor, indication, max_trials) with examples and defaults. The tool description reiterates that filtering is possible by sponsor, indication, drug, or NCT id, but adds no new semantics beyond the schema. Since coverage is 100%, the baseline of 3 is appropriate.

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 clearly states the tool performs clinical-stage due diligence by combining ClinicalTrials.gov trial landscape and FDA openFDA facts (label, approval history, FAERS adverse events, recalls) into a machine-formatted DD brief. It distinguishes its scope from sibling tools like edgar_financials or edgar_report by explicitly naming the clinical data sources and the resulting brief.

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 implies use for clinical due-diligence needs but does not explicitly state when to choose this tool over alternatives, nor does it provide example filters or conditions. It does mention keyless access and payment settlement, which gives some operational guidance, but lacks explicit when-to-use/when-not-to-use instructions.

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