Knowledge Graph Visualization

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

With no annotations, the description must disclose behavioral traits. It only indicates a read operation (get) but omits details on side effects, authentication requirements, rate limits, or behavior with empty graphs. The single sentence is insufficient for a tool with no annotation support.

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 very concise at 10 words, but it lacks necessary details about the output structure or usage context. While front-loaded, it is too sparse for a tool that would benefit from more explanation.

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 simplicity (one optional parameter, no output schema), the description fails to explain the output format (e.g., structure of nodes and edges) or any constraints. Users are not told what the returned data looks like.

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 coverage is 100%, with one parameter 'format' well-defined by enum values. The description adds no additional meaning beyond the schema, so a baseline score of 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 clearly states the tool gets a knowledge graph structure for visualization, specifying nodes and edges. It distinguishes from siblings like alg-build-knowledge-graph by its focus on retrieval for visualization, but does not explicitly differentiate from alg-get-specialist-knowledge.

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, such as alg-build-knowledge-graph or alg-get-specialist-knowledge. There is no mention of prerequisites, like whether the graph needs to be built first.

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