brain_graph

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

No annotations are provided, so the description carries full burden. It transparently describes the output structure and schema, but does not disclose behavioral traits such as whether the operation is read-only, required permissions, or side effects on the brain graph. The agent cannot assess safety from the description alone.

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 efficient, with two information-rich sentences and a line of examples. Every sentence adds value: purpose, schema details, and example usage. No redundancy or fluff.

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 explains the output structure (nodes, links, attributes) and format options (json/summary) thoroughly, compensating for the lack of an output schema. However, it omits details like error handling, performance characteristics, or constraints beyond max_nodes.

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% (all five parameters have descriptions). The description adds marginal value with example invocations and clarifies defaults like max_nodes=400, but does not substantially enhance understanding beyond what the schema already provides. 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 clearly states the tool exports a Causal Knowledge Graph as a 3D-render-ready payload, specifying the schema, node/link attributes, and target frontends. It is a specific verb-resource combination that distinguishes it from siblings like ckg_inspect or brain_search.

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 use for obtaining a renderable graph but does not explicitly state when to use this tool over alternatives (e.g., ckg_inspect) nor when not to use it. The context of 'data layer behind the brain viz' is clear but lacks exclusionary guidance.

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