get_graph_labels

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

With no annotations, the description must carry the behavioral burden. It usefully discloses that output 'can be long on a large knowledge base' and that the result is 'currently' in the graph, implying a live snapshot. It does not explicitly mention read-only behavior or pagination, but the read-only nature is strongly implied by 'List' and the output schema covers the return structure.

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?

Two sentences, no filler. The core purpose is front-loaded, and the second sentence adds an actionable caveat plus alternative tool names. Every word earns its place.

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?

For a zero-parameter read-only listing tool with an output schema, the description is fully sufficient. It states what is returned, warns about scale, and directs users to more targeted siblings when appropriate.

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 tool has zero parameters, so the baseline is 4. The description correctly adds no parameter information because none is needed; the empty schema already fully covers the parameter space.

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 uses a specific verb ('List'), a clear resource ('entity label (name)'), and a precise scope ('every ... currently in the knowledge graph'). It also differentiates itself from sibling tools by emphasizing 'every', which distinguishes it from get_popular_labels and search_labels.

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 gives explicit when-not-to-use guidance: 'Can be long on a large knowledge base -- prefer get_popular_labels or search_labels when looking for something specific.' This clearly routes an agent to the appropriate alternatives while implying this tool is for complete enumeration.

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