spanning_tree

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

With no annotations, the description must disclose behavioral traits but only states the computation type. It does not describe what the tool returns (e.g., list of edges, total weight), whether it mutates state, or any side effects. The maximize parameter hints at dual behavior but lacks detail.

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 sentence, which is concise and front-loaded, but it omits critical details that make it under-specified. It earns its place but does not fully inform the agent.

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 the tool has 4 parameters, no annotations, an output schema (unseen), and numerous sibling tools, the description is incomplete. It lacks explanation of input format, output, and usage 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?

Schema description coverage is 0%, so the description must compensate but does not. The parameter names (edges, weights, maximize, edge_weights_attr) offer some hint, but 'edge_weights_attr' is ambiguous and no explanation is provided for how to structure input or the effect of each parameter.

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 computes a minimum or maximum spanning tree, which is a specific graph algorithm. It uses a specific verb ('compute') and resource ('spanning tree'), and distinguishes between two modes, but does not explicitly differentiate from sibling graph tools like graph_create or shortest_path.

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?

No guidance is given on when to use this tool versus alternatives. There is no mention of prerequisites (e.g., graph connectivity) or situations where other tools like shortest_path would be more appropriate.

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