aggregate_graph

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

With no annotations provided, the description must convey behavioral traits. It indicates the tool is a read operation ('Retrieve') and efficient for aggregation, but does not disclose idempotency, side effects, or any access constraints. The description adds some context but leaves gaps.

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 consists of two concise sentences, front-loaded with the core purpose and optimization context. Every sentence adds value, and there is no extraneous 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?

The description lacks output details; it doesn't mention the format or structure of returned nodes, which is critical for a tool intended for aggregation and map-reduce tasks. Without an output schema, this omission reduces 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?

The input schema has 100% coverage, so parameters are already well-documented. The description only repeats that filtering by node_type and tags is supported, adding no new semantic information beyond the schema.

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 retrieves a 'broad set of nodes' bypassing 'standard semantic limits', making it distinct from sibling tools like query_graph and get_related. It also specifies optimization for global aggregation and map-reduce tasks, which uniquely identifies its purpose.

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 large-scale aggregation tasks by mentioning 'bypassing standard semantic limits' and 'optimized for global aggregation and map-reduce'. However, it does not explicitly state when not to use it or name alternative tools, which would strengthen guidance.

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