get_memory_graph

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

Annotations already provide comprehensive behavioral hints (readOnlyHint: true, destructiveHint: false, idempotentHint: true, openWorldHint: false). The description adds value by specifying the tool retrieves '메모리 지식 그래프' (memory knowledge graph) and provides usage examples that clarify it can retrieve either the entire graph or start from a specific key. This adds useful context beyond what annotations provide about the tool's scope and typical use cases.

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 appropriately sized with a clear purpose statement followed by keywords and usage examples. The structure is front-loaded with the core purpose first. The keywords section could be more concise, but overall the description avoids unnecessary verbosity while providing useful 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?

Given the comprehensive annotations (which cover safety and behavioral aspects) and 100% schema description coverage, the description provides adequate context. The lack of an output schema means the description doesn't explain return values, but this is acceptable given the annotations indicate it's a read-only operation. The description could be more complete by explicitly differentiating from sibling tools, but it provides sufficient context for basic usage.

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?

With 100% schema description coverage, the input schema already fully documents all 4 parameters. The description doesn't add any additional parameter semantics beyond what's in the schema descriptions. The usage examples imply parameter usage (e.g., 'project-architecture의 관계 그래프 보여줘' suggests using the 'key' parameter), but don't provide new information about parameter meaning or behavior.

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's purpose as '메모리 지식 그래프를 조회합니다' (retrieves memory knowledge graph), which is a specific verb+resource combination. However, it doesn't explicitly differentiate this from sibling tools like 'analyze_dependency_graph' or 'list_memories', which might have overlapping functionality. The keywords provide additional context but don't enhance the core purpose statement.

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 usage examples that imply when to use this tool (e.g., '전체 메모리 그래프 조회' for retrieving the entire graph), but doesn't explicitly state when to use it versus alternatives like 'analyze_dependency_graph' or 'list_memories'. The examples give contextual guidance but lack explicit when/when-not statements or named alternatives.

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