register_entity

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

No annotations are provided, so the description carries the full burden. It does disclose that the registration affects future lookups, but it lacks detail on side effects like overwriting behavior, idempotency, or persistence. The core behavior is clear, but deeper behavioral context is missing.

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 extremely concise, consisting of two short sentences that front-load the purpose and usage. Every word earns its place, with no redundancy or filler.

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 tool has 4 parameters, no annotations, and no output schema, making the description the sole source of guidance. It covers the basic action and when to call it, but omits parameter semantics and potential edge cases, leaving the agent under-informed for a tool with this complexity.

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%, yet the description provides no explanations for the parameters (id, name, system, attributes). It doesn't clarify what 'system' refers to or how 'attributes' are used, leaving the agent without sufficient meaning beyond the field names.

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: to register a known good entity into resolver memory for future lookups. The verb 'register' is specific and the resource is well-defined, distinguishing it from siblings like resolve_entity or fuzzy_match_records.

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 'Call this after a human confirms a match' provides explicit guidance on when to use the tool. It implies not to use it before confirmation, though it doesn't name alternative tools or list when-not scenarios.

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