recommend_ecosystem

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

The description states 'It has no side effects', which is good. However, with no annotations provided, it lacks disclosure of authorization requirements, error behaviors, or potential impacts on the system.

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 (~100 words), structured into two paragraphs with a clear first sentence front-loading the purpose, followed by parameter details and return type. No superfluous content.

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, and an output schema, the description adequately covers input semantics and side-effect status. It mentions the return type but does not detail structure, which is partially acceptable due to presence of output schema.

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 compensates fully by explaining each parameter: workspace as absolute path, goal as target capability, limit as max recommendations, and live for real-time vs offline mode. This adds significant meaning beyond the schema.

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 action 'Recommend' and the resource 'compatible MCP servers, skills, repositories, and APIs', which is specific and distinct from sibling tools like analyze_workspace or audit_trust_surface.

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 implies use for recommending external integrations matching a project profile, but it does not explicitly state when to use this tool versus alternatives, nor does it provide when-not scenarios or exclusions.

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