get_analytics_raw

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 implies a pass-through to the DHIS2 analytics API but does not explicitly state read-only behavior, rate limits, or side effects. The description adds some context but lacks full behavioral disclosure.

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 and front-loaded with purpose. Each sentence adds value, including an example. It could be slightly more compact, but it remains efficient.

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?

Although an output schema exists (so return values need not be explained), the description does not cover the 'output_scheme' parameter, potential error conditions, or format validation for dimension strings. This leaves some gaps for a tool intended for advanced, raw usage.

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%, but the description adds significant meaning for 'dimensions' (with an example of raw strings) and 'filters' (explaining their purpose). However, 'output_scheme' is left unexplained. Overall, it compensates well for the lack of schema descriptions.

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 'Advanced analytics call with full control over dimensions', distinguishing it from the sibling tool get_analytics by explicitly stating 'Prefer get_analytics for the common case'. The verb 'analytics call' and resource 'dimensions' are specific.

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 provides explicit guidance: 'Pass raw dimension strings exactly as the DHIS2 analytics API expects' with an example, explains the use of filters, and advises when to use the alternative tool ('Prefer get_analytics for the common case').

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