lbb_decode

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

Annotations already indicate readOnlyHint=true, so the description adds little beyond mentioning that types may be resolved from entity names. It does not contradict annotations, but also does not enrich behavioral context significantly.

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 sentence that front-loads the main action. It is concise with no wasted words, but could benefit from minor structuring to separate purpose from optional behaviors.

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 complexity (8 parameters, no output schema), the description is incomplete. It does not explain output format, default behaviors, or how to use optional parameters like detail and graph, leaving significant gaps.

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 description only implicitly covers source_name and target_name, while the schema has 8 parameters with only 38% coverage. No explanation is given for graph, branch, detail, source_type, target_type, or use_model_when_forced, leaving the agent uncertain about their purpose.

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: naming the relation between two entities using a controlled vocabulary. It mentions that types can be omitted, which adds specificity. However, it does not explicitly distinguish from sibling tools, though the task is unique.

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 like lbb_search or lbb_query. There is no mention of when not to use it or how it fits into a workflow.

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