cross_connect

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

There are no annotations, so the description carries the full burden of behavioral disclosure. 'Add relations' signals a mutation, but the description does not state whether entities must already exist, whether the operation is reversible, whether duplicates are allowed, or what side effects occur. For a write operation with no annotations, this is a significant transparency gap.

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, focused sentence with no filler or repetition. It front-loads the key action ('Add relations') and immediately ties the tool to its candidate source. Every word contributes to the core meaning.

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 mutation tool with no annotations and no output schema, one short sentence leaves too much unspecified. The description does not cover the input structure, required fields, dataset parameter, or what the agent should expect after invocation. It is adequate only if the agent already knows the memify_candidates output format and the relation semantics.

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 description coverage is 0%, so the description must compensate, but it adds little parameter-level meaning. It clarifies that source and target are existing entities and that relations come from candidates, but it does not explain the required fields (source, name, target) or optional fields (evidence, description). The schema provides only names and defaults, not behavioral meaning.

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 ('Add relations') and a clear resource ('existing entities'), and references memify_candidates as the source of proposals. This distinguishes it from memify_candidates, which proposes candidates, while cross_connect applies them. It could be slightly clearer about what 'relations' means, but the core purpose is understandable.

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 phrase 'proposed by memify_candidates(cross_connect)' implies that this tool should be used after memify_candidates has generated relation candidates. However, there is no explicit statement about when not to use it or what alternatives exist beyond the sibling list. The usage context is implied rather than directly stated.

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