List tool-selection guidance

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

The readOnlyHint annotation already establishes the safe-read profile. The description adds useful behavioral context by explaining that the result is an index of preferred tools, anti-patterns, and reasons, and that filtering narrows the list. It does not cover exhaustiveness or staleness, but the output schema likely handles return structure.

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?

Two sentences with no filler: the purpose and return format are front-loaded, followed by concise filter guidance. Every sentence earns its place.

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?

With zero required parameters, a complete input schema, an output schema, and readOnlyHint, the description is largely complete for correct invocation. It could explicitly state that omitting filters returns the full index, but that is a minor gap.

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%, so both the substring behavior of `intent` and the exact-match behavior of `category` are already documented in the schema. The description repeats the filtering purpose but adds no syntax, examples, or constraints beyond what the schema provides.

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 states a specific verb ('Return') and resource ('intent → preferred-tool index'), and it positions the tool as the way to choose among bash-mcp siblings. It also specifies what each entry contains: preferred tool, raw-command anti-patterns, and rationale.

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?

It clearly implies when to use the tool: to pick the right bash-mcp tool for a goal and to avoid raw-command anti-patterns. It does not explicitly state when not to use it or name a direct alternative, but the meta-tool purpose makes the usage context obvious.

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