link

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

The description adds behavioral details beyond annotations: self-links rejected, canonicalization of 'related' type, and normalization of task_ref to lowercase kebab-case. No contradiction with annotations.

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 highly concise: three sentences cover purpose, kinds, constraints, and normalization. No superfluous information.

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?

The description covers the core behavior and constraints but omits error handling (e.g., self-links, duplicate links) and does not explain the output schema. Given the output schema exists, return values are not required, but side effects and edge cases are lacking.

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?

With zero schema description coverage, the description must compensate, but it only partially explains parameters. It details 'kind' and 'task_ref' but does not describe 'source_id' and 'target_id' beyond being IDs of ideas.

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 connects two ideas and enumerates the four kinds of relationships. It also includes canonicalization and self-link rejection. However, the sibling tool 'related' shares a name with one of the kinds, which may cause ambiguity.

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 contextual clues for when to use (when current work reveals a relationship) but does not explicitly mention when not to use or compare with alternative tools like the sibling 'related'.

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