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

With no annotations, the description carries the behavioral burden. It usefully discloses that the tool is a no-op with a reason when the graph is not enabled and that predicate must be registered. However, it does not disclose duplicate or overwrite behavior, entity existence requirements, or side effects beyond graph creation.

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?

Four short sentences, each earning its place: purpose, no-op behavior, usage scenario, and predicate constraint. The description is front-loaded and contains no filler or redundancy.

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 is adequate for invoking a simple relation-recording tool, and the output schema reduces the need to explain return values. It leaves gaps around duplicate relationships, whether entities must already exist, and how this relates to memory_graph_related, which matter for a write operation with no annotations.

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 high, so the baseline is 3. The description adds value by giving a concrete triple example ('alice -> works_on -> teamshared') and by adding the constraint that predicate must be a registered link type, which the schema itself does not state.

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 starts with a specific verb and resource: 'Record an explicit relationship in the optional org-scoped graph store.' This makes the tool's core purpose clear, but it does not explicitly differentiate it from the sibling memory_graph_related, so the agent must infer the distinction from the verb 'Record.'

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?

It gives an explicit use case ('Use this when you learn a structured fact ... that vector recall would obscure') and points the agent to memory_ontology_list for predicate validation. It does not explain when not to use it or how it compares to memory_graph_related, but the guidance is clear and actionable.

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