remove_individual

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

With no annotations, the description carries the full burden. It explicitly states that removing an individual also removes all connected facts (edges), which is a critical behavioral trait. It also provides examples showing different formats for the individual_id. However, it does not mention permissions, reversibility, or other side effects like cascading to dependent individuals or model integrity constraints.

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 well-structured with a lead sentence, a critical note, then Args/Returns/Examples. It is somewhat lengthy due to multiple examples, but each example adds value by illustrating common patterns. It could be slightly more concise, but the examples justify the length.

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 purpose, cascading behavior, parameter formats, and return value. It lacks information about error handling, prerequisites (e.g., model existence), and whether the operation is reversible. Given the simple parameters and presence of an output schema, it is nearly complete but missing some edge-case context.

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 schema description coverage is 0%, so the description must bear the load. It includes an Args section explaining both parameters and provides rich examples showing multiple valid formats for individual_id (variable reference, full ID, evidence individual). This goes far beyond the schema's minimal info and clarifies usage patterns.

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 action ('Remove an individual from a GO-CAM model') and notes the cascading removal of connected facts. This differentiates it from sibling tools like remove_fact (which removes a single fact) and add_individual (which adds). The verb and resource are specific, and the note adds crucial context.

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 implicitly tells when to use this tool (when you want to remove an individual and all its edges) but does not explicitly state when to prefer it over alternatives like remove_fact or add_individual. The examples show usage but lack explicit 'use when' or 'do not use when' guidance.

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