suggest_plugins

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

No annotations are provided, so the description fully bears the burden. It explains the scoring mechanism (word matching with 3x weight on plugin names), sorting by relevance, and gives examples. This provides comprehensive insight into the tool's behavior without contradiction.

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 well-structured: purpose, usage guidelines, behavioral details, examples, and parameter definitions. Every sentence adds value without repetition, and it remains concise while covering all essential aspects.

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 simplicity of the tool (2 parameters, one required) and the presence of an output schema (not shown but noted), the description provides complete contextual information. It explains when to use it, how it works, and what parameters are needed, leaving no critical gaps for an AI agent.

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?

With 0% schema description coverage, the description adds necessary meaning: 'task: natural language description of the project or need' and 'limit: max results to return (default 5)'. This is helpful but could be slightly more detailed about the task format or limit constraints.

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?

Clearly states the tool's function: 'Suggest gen-e2 plugins relevant to a natural language task or project description.' Uses a specific verb (suggest) and resource (plugins), and distinguishes from the related sibling 'suggest_entries' by emphasizing plugin-level discovery before drilling into individual artefacts.

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?

Explicitly tells when to use the tool: 'Use this for plugin-level discovery when the user describes their project or use case and wants to know which plugins are most relevant — before drilling into individual artefacts with suggest_entries.' Also provides examples of typical inputs and outputs, giving clear context for appropriate invocation.

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