counterfactual_query

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

With no annotations provided, the description carries full burden. It explicitly states the tool is pure and does not mutate the graph, which is critical behavioral transparency. It also explains the semantics of the returned chains. However, it does not disclose error behavior, performance implications, or prerequisites for the graph state.

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 concise, containing one sentence with an embedded example. It is front-loaded with the key question. However, the '3B.6' prefix is somewhat odd and unnecessary, slightly detracting from structure. Overall it is efficient but not perfectly structured.

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?

Given 5 parameters (4 required) and no output schema, the description is too brief. It does not explain the return format (are chains lists of node IDs?), nor does it detail the maxDepth parameter's effect. The example provides context but leaves significant gaps for an agent to correctly invoke the tool.

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. It only mentions parameter names in an example but provides no formal definitions or constraints beyond what the names imply. The maxDepth parameter is not explained. The description adds minimal value for understanding individual parameters.

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: it performs a counterfactual query to check reachability after removing an edge. It uses specific verbs ('returns chains') and identifies the resource (graph reachability), distinguishing it from sibling tools that mutate the graph or are purely navigational.

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 provides a concrete example ('What if we remove edge...?') implying when to use this tool, but it does not explicitly state when NOT to use it or suggest alternatives. An agent can infer usage from the example, but explicit guidelines are missing.

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