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

Annotations indicate read-only, idempotent, and non-destructive. The description adds behavioral details: pulls latest 10-K data for companies with correct fiscal year handling, FAERS data for drugs, results sorted by primary metric, and returns paired data with citation URIs. No contradictions with annotations.

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 relatively compact (4 sentences) and front-loaded with trigger phrases. Every sentence adds value: trigger examples, usage preference, data sources per type, sorting, and return format. Could be slightly more concise but still effective.

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 explains return format ('paired data + pipeworx:// citation URIs per entity'). It covers entity types, data sources, fiscal year handling for companies, and metric sorting. The tool's purpose and behavior are fully described.

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% with clear parameter descriptions. The description adds meaning beyond schema: for 'type', it explains what data is pulled for company vs drug (SEC EDGAR/XBRL financials, FAERS counts) and for 'values', it gives examples (tickers for companies, drug names). It also describes sorting behavior.

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 specific verbs like 'Compare' and provides trigger examples ('X vs Y', 'rank these companies'). It clearly states the tool compares 2-5 companies or drugs in one call, and explicitly distinguishes from sequential lookups by saying 'ALWAYS PREFER over sequential single-pack lookups'.

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 gives explicit guidance on when to use: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' It provides concrete use cases like 'which is bigger / better / larger / more profitable' and specifies the number of entities (2-5). It implicitly advises against using for single-entity queries.

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