read_graph

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

With no annotations provided, the description carries the full burden. It discloses that the tool reads data (implying non-destructive) and returns a complete graph, but lacks details on permissions, rate limits, or error handling. It adds some context about what's included (decay scores, statistics) but is incomplete for behavioral transparency.

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 well-structured and front-loaded with the core purpose, followed by parameter and return details. Every sentence adds value without redundancy, making it efficient and easy to parse for an agent.

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 tool's moderate complexity (3 parameters, no annotations, but with an output schema), the description is fairly complete. It covers purpose, parameters, and return values, and the output schema reduces the need to explain returns in detail. However, it lacks usage guidelines and some behavioral context, slightly impacting 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 schema description coverage is 0%, so the description must compensate. It explains all three parameters: status filters memories by specific values, include_scores adds decay scores and age, and limit sets a maximum return count. This adds meaningful semantics beyond the bare schema, though it could elaborate on default behaviors or constraints.

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 verb 'Read' and the resource 'entire knowledge graph of memories and relations', specifying it returns the complete graph structure including memories with decay scores, relations, and statistics. This distinguishes it from siblings like search_memory or cluster_memories by emphasizing comprehensive retrieval rather than filtering or processing.

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 versus alternatives. It does not mention scenarios where this is preferred over search_memory or open_memories, nor does it specify prerequisites or exclusions, leaving the agent to infer usage from the purpose alone.

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