get_best_practices

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

With no annotations, the description carries the full burden. It states the return format (JSON string) and the tool's input, implying a read-only operation. It does not elaborate on side effects or errors, but for a simple get tool this is adequate.

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, using a docstring format with brief explanation, args, and returns. No unnecessary information, every sentence is informative.

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's simplicity (one parameter, no required arguments, output schema exists), the description covers purpose, parameter behavior, and return type adequately. No gaps for typical usage.

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 0%, so the description must add meaning. It fully explains the topic parameter: optional, with examples and behavior when None. This goes beyond the schema, which only shows type and default.

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 returns MCP server development best practices, using the specific verb 'Get' and resource 'best practices'. It also mentions optional topic filtering, distinguishing it from sibling tools like get_implementation_guide.

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 context on when to use the tool (to get best practices) and mentions optional topic selection, but does not explicitly state when not to use it or compare with alternatives like get_implementation_guide.

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