read_graph

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

No annotations are provided, so the description carries the behavioral disclosure burden. It discloses the return payload shape and raises ValueError for invalid status values or out-of-range limits. It does not mention auth, rate limits, or side effects, but the read-oriented behavior is adequately conveyed.

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 compact and well-organized: one-sentence purpose, a scannable Args list, Returns, and Raises. Every sentence adds meaningful information without filler.

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 5 parameters, no annotations, and a rich sibling set, this description covers parameter meaning, defaults, output shape, and error behavior. An agent has enough information to invoke the tool correctly without needing additional context.

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%, yet the description fully documents every parameter: status options, include_scores meaning, limit range, page indexing, and page_size cap. This is high-value semantic detail that the bare schema completely lacks.

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, 'Return,' and a specific resource, 'entire knowledge graph with memories and relations.' This clearly distinguishes the tool's scope from sibling search-oriented tools.

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 phrase 'entire knowledge graph' implies this tool is for full-graph retrieval, whereas siblings like search_memory suggest targeted lookup. However, the description does not explicitly state when to use this tool instead of alternatives or when not to use it.

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