generate_knowledge_graph

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'generate' and 'for visualization', implying a read-only operation that produces data, but fails to specify critical details such as whether this is a computationally intensive process, if it requires specific data inputs (e.g., existing notes), or what the output entails (e.g., structure, size limits). This leaves significant gaps for a tool with potential complexity.

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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and easy to parse, though it could be slightly more informative without sacrificing brevity.

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 lack of annotations and output schema, the description is incomplete for a tool that likely involves graph generation—a non-trivial operation. It doesn't explain what 'knowledge graph data' means in this context, how it's derived (e.g., from notes, tags), or what the output looks like, leaving the agent with insufficient context for effective use.

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 has 100% description coverage, with clear documentation for both parameters ('format' and 'includeOrphans'). The description adds no parameter-specific information beyond what the schema provides, so it meets the baseline score of 3 for adequate but non-additive coverage.

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 the tool 'generate[s] knowledge graph data for visualization', which provides a clear verb ('generate') and resource ('knowledge graph data') but lacks specificity about what constitutes 'knowledge graph data' or how it relates to the sibling tools. It distinguishes itself from obvious non-siblings (e.g., 'create_note'), but doesn't clarify its unique role versus tools like 'analyze_note_relationships' or 'suggest_connections' that might involve graph-like operations.

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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, typical use cases, or comparisons to sibling tools like 'analyze_note_relationships' or 'suggest_connections', leaving the agent to infer usage based on the name alone.

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