AI agents and their MCP servers

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

Annotations already declare readOnly/idempotent/non-destructive/openWorld=false, so safety is covered. The description adds genuine behavioral context beyond them: the default output is pruned to agents, MCP servers and network-active processes, which materially shapes what the agent will receive. It stops short of describing ordering, depth limits, or volume characteristics.

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?

Front-loaded with the core action and contents, followed by routing guidance and the default-scope caveat. Three sentences, no filler, and the parenthetical product list earns its space by aiding recognition.

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?

For a read-only listing tool with no output schema, the description fully covers what the returned trees contain and how they are scoped by default, while annotations carry the safety profile. An agent has everything needed to invoke and interpret it.

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 100% and the single parameter's description already explains the default and the tracing use case. The description's mention of pruning restates the same default rather than adding format or syntax detail, so the baseline 3 is appropriate.

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?

States a specific verb (list) and resource (process trees of running AI agents), then enumerates exactly what each tree contains: the agent, its MCP servers, spawned programs, and network connections. It explicitly contrasts itself with list_connections and explain_process, so an agent can route correctly without opening any schema.

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?

Gives a positive trigger ('Use this to see which agent or MCP server a process or connection belongs to') plus two explicit alternatives with their selecting conditions: list_connections for every connection on the PC, explain_process for one process in depth. Nothing is left to inference.

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