nih_projects_by_agency

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

Annotations provide readOnlyHint=true, so the safety profile is covered. The description adds context that the results show which institutes fund the most research, giving meaning to the counts. However, it does not disclose any other behavior (e.g., defaults for agencies, pagination, or performance), though the schema covers the agencies default. It adds some value but not rich.

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 three short sentences, front-loaded with the main action, then benefits and use case. No filler or redundancy. Each sentence adds value.

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 read-only count aggregation tool, the description covers the core purpose, output type (counts), and context. The schema covers required fiscal_year and optional agencies. It doesn't explain return format or finer details, but that's acceptable given no output schema and modest complexity. Missing a bit on how counts are organized (per agency), but 'by institute/center' covers that.

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 100%, so the schema already documents fiscal_year and agencies (including the default 'top 25'). The description's mention of 'fiscal year' does not add new meaning beyond the schema. It gives examples of institutes but not param-specific guidance. 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 opens with a specific verb and resource: 'Get project counts by NIH institute/center for a fiscal year.' It clearly distinguishes its aggregated-count purpose from sibling tools like 'nih_search_projects' (search projects) and 'nih_spending_by_category' (spending categories). It adds examples of agency codes to clarify output.

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 includes an explicit use case: 'Useful for understanding NIH budget allocation across disease areas.' This implies when to use the tool, but it doesn't mention alternatives or exclusions (e.g., when you need project-level detail). Clear context but no direct comparison to siblings.

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