Serena MCP Server

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns instructions (not performing the onboarding itself) and has a usage limit (once per conversation), which adds useful behavioral context. However, it doesn't cover potential side effects, error conditions, or what 'instructions' entail, leaving gaps for a mutation-related tool.

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 highly concise and well-structured with two sentences: the first states when to use it, and the second covers usage frequency and return value. Every sentence adds essential information without redundancy, making it front-loaded and efficient.

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 complexity (likely low, with 0 parameters) and no annotations or output schema, the description is somewhat complete but has gaps. It explains when and how often to use it and what it returns, but doesn't detail the format of 'instructions' or potential errors. For a tool that might involve setup or configuration, more context on outcomes would be beneficial.

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?

The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't discuss parameters, which is appropriate. A baseline of 4 is applied since it compensates adequately for the lack of parameters by focusing on usage context.

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: to be called when onboarding hasn't been performed yet, and it returns instructions for creating onboarding information. It uses specific verbs ('call', 'returns') and identifies the resource (onboarding information). However, it doesn't explicitly differentiate itself from sibling tools like 'check_onboarding_performed' or 'initial_instructions', which prevents a perfect score.

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 explicit usage guidelines: 'Call this tool if onboarding was not performed yet' and 'You will call this tool at most once per conversation.' This clearly defines when to use it (onboarding not done) and includes a usage constraint (once per conversation), though it doesn't mention alternatives like 'check_onboarding_performed'.

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