get_knowledge_graph

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

Annotations already mark the tool as read-only and non-destructive, and the description reinforces this with 'Read-only.' It adds valuable behavioral context beyond annotations by disclosing the enhanced-intelligence prerequisite and prior entity-extraction dependency, and by specifying the exact node/edge return shape.

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 efficiently organized: purpose first, then use case, prerequisite, read-only note, and return shape. Every sentence contributes meaningful information, though the 'Read-only' sentence is redundant with annotations and could be omitted.

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, the description covers the main invocation context: what it returns, when to use it, the required mode, and read-only behavior. The schema covers all parameter semantics. A minor gap is lack of guidance on alternative tools for similar graph/connection tasks, but overall the tool is well specified.

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 input schema already provides 100% coverage with detailed descriptions for all four parameters, including ranges, defaults, filter semantics, and example values. The description adds no additional parameter-level meaning, so 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 opens with a specific verb and resource: 'Build a knowledge graph from stored memories.' It clearly distinguishes itself from sibling memory retrieval tools by emphasizing entities-as-nodes/relationships-as-edges and the use case of visualizing connections between concepts.

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 explicitly states when to use the tool: 'Use for visualizing connections between concepts.' It also provides a critical prerequisite: 'Requires enhanced intelligence mode with prior entity extraction.' However, it does not explicitly mention alternatives or when-not-to-use scenarios relative to siblings like find_connections.

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