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

With no annotations, the description carries the burden and discloses that this is a pure DB read with 0 credits and no cost. It also explains that caller-specific identities are returned, which is useful behavioral context, though it does not describe rate limits or output structure in detail.

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 front-loaded and appropriately short, but the final 'Free.' fragment is redundant with '0 credits' and does not add information. Otherwise every sentence contributes to understanding the tool.

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 parameterless help tool with no output schema, the description is complete: it says what is returned, how the returned identities should be used, and that the operation is a free read. Nothing essential for correct invocation is missing.

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 tool has zero parameters, so there are no parameter semantics to explain. The baseline for a parameterless tool is 4, and the description does not need to compensate for missing schema coverage.

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 states a specific verb and resource: it returns the engagement graph schema, FK edges, and canonical SQL examples for use with traverse_graph. It also names the caller-specific identities returned, making the tool's purpose distinct from the execution sibling traverse_graph.

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?

It clearly frames the tool as preparation for writing a SELECT against the engagement graph via traverse_graph, and tells the caller to substitute returned identities into example SQL. It does not explicitly state when not to use it or name alternatives, but the context is clear.

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