signal_check

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

With no annotations, the description carries the full burden and does disclose key behavior: it computes PRR, ROR, 95% confidence intervals, Yates chi-squared, and Evans signal criteria. It does not describe data recency, minimum case thresholds, or what happens when a drug-reaction pair has sparse or no reports, leaving some operational gaps.

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 two efficiently packed sentences with no filler. The tool's purpose and analytical outputs are front-loaded, followed by the critical input-format constraint.

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 statistical lookup tool with an output schema, the description provides enough context to invoke it correctly: FAERS source, required MedDRA vocabulary, and the returned signal metrics. It is slightly incomplete on drug name formatting and edge-case behavior, but the output schema covers return-value details.

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 parameter meaning. It explains the reaction parameter well by requiring MedDRA preferred terms and giving 'PANCREATITIS' as an example, but it says nothing about drug name format or normalization, leaving one of the two required parameters under-specified.

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 uses a specific verb-resource pairing: 'Pharmacovigilance signal check for a drug-reaction pair in FAERS', and names the exact statistics produced (PRR, ROR, confidence intervals, Yates chi-squared, Evans criteria). This is clearly distinct from siblings such as search_drug_labels and get_adverse_events.

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?

It gives clear context for use (FAERS disproportionality analysis) and specifies the necessary input vocabulary: 'Use MedDRA preferred terms, e.g. PANCREATITIS'. It does not explicitly state when not to use it or name alternatives, but no sibling tool performs signal detection, so the guidance is sufficient.

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