aggregate_sift

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

No annotations are provided. The description explains the tool runs an aggregation and returns rows, but does not disclose destructive potential, authorization needs, or performance implications. With zero annotation coverage, the description is adequate but not thorough.

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 highly concise: 3 sentences with a clear structure (purpose, parameter definitions, return). The example is front-loaded. No superfluous 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 complexity of MongoDB aggregation and no output schema, the description covers the main aspects: operation type, key parameters, return type. The example aids understanding. However, it could mention validation, error handling, or that the pipeline must be valid aggregation stages.

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 explain parameters. It defines both sift_id and pipeline, and provides a concrete example of pipeline format. This adds significant value beyond the schema, though more detail on pipeline constraints would improve it.

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 runs a MongoDB aggregation pipeline against a sift's records. It uses specific verb 'run' and resource 'aggregation pipeline against sift records', distinguishing it from siblings like query_sift or find_records.

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 no guidance on when to use this tool vs alternatives (e.g., query_sift, find_records). It doesn't mention prerequisites, context, or when not to use aggregation. Agents receive no decision support.

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