Drug Interaction Checker

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

No annotations are provided, so the description carries the full burden. It discloses output details (severity levels, mechanism, citations) and instructs to include a disclaimer, but lacks information on side effects, idempotency, or other behavioral traits.

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 concise (two sentences), with the first sentence covering purpose and output, and the second an agent instruction. It is front-loaded and efficient, though could be slightly more structured.

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 and no annotations, the description is fairly complete about return values (severity, mechanism, citations, disclaimer). However, it omits error handling, prerequisites, or rate limits, which are not critical but would enhance completeness.

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. It mentions 'by brand or generic name' but does not provide per-parameter details or constraints beyond the schema. This adds minimal value for two undocumented string parameters.

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 checks interactions between two drugs, specifies inputs (brand or generic names), and lists output details (severity, mechanism, citations). It distinguishes from sibling tools like 'check_interactions_multi' (multiple pairs) and 'normalize_drug_name' (name normalization).

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 usage for a single pair of drugs but does not explicitly state when to use this tool over 'check_interactions_multi' or when not to use it. No alternatives or exclusions are mentioned.

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

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

No annotations are provided, so the description carries the full burden. It discloses that it returns one entry per unordered pair and deduplicates A-B/B-A, and sets a limit. However, it lacks information on read-only nature, error handling, or output format.

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 extremely concise with two sentences. The first sentence states the purpose, and the second adds key behavioral details. No redundant 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?

Given the moderate complexity and lack of output schema, the description covers the main purpose and key behaviors but does not explain the return structure or error cases. It is complete enough for a simple tool but leaves gaps about expected output.

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?

With 0% schema description coverage, the description adds meaning by clarifying that the 'drugs' array contains drug names and emphasizes the 8-drug limit. It also mentions deduplication behavior related to pairs, providing context beyond the schema's type and constraints.

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 a pairwise interaction check across a list of drugs (polypharmacy). It uses specific verb 'check' and resource 'interactions' and distinguishes from its sibling 'check_interaction' which is singular.

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 explicitly mentions the use case: multiple drugs for polypharmacy, and specifies a limit of 8 drugs. It implies this is for batch checking, while sibling 'check_interaction' is for single pairs. However, it doesn't explicitly state when not to use or give alternatives.

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

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

No annotations are provided, so the description carries the full burden. It discloses the output structure (RxCUI, generic name, brand names, synonyms) but does not mention behavior on invalid input, whether it is read-only, or any side effects. It is adequate but not explicit about safety or error cases.

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, well-structured sentence that front-loads the action and output. No redundancy or unnecessary words.

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 simple single-parameter lookup tool, the description covers the purpose, input, and output. It lacks explicit mention of error handling or not-found cases, but is largely complete given the tool's simplicity and the presence of sibling tools.

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% for the single parameter 'name', which already includes a description and example. The description adds little beyond restating the parameter's role in context. Baseline 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 action ('resolve'), the input ('brand or generic drug name'), and output ('canonical RxNorm record: RxCUI, generic name, brand names, synonyms'). It distinguishes from sibling tools (check_interaction, check_interactions_multi) which focus on interactions, not name normalization.

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 usage for drug name normalization, but does not explicitly state when to use it versus siblings, nor provide conditions or exclusions (e.g., 'Use this when you need to map a drug name to its standard form; for interactions, use check_interaction').

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