recommend

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that recommendations are based on current task and dependencies and that 'Same scenario is not recommended twice,' which adds some context about uniqueness and input-based behavior. However, it lacks details on permissions, rate limits, error handling, or what the output looks like (e.g., format of recommendations), which is a significant gap for a tool with no annotation coverage.

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 and front-loaded, stating the core purpose in the first sentence. The second sentence elaborates on the types of tools/services, and the third adds a behavioral note about not repeating scenarios. Each sentence adds value without redundancy, making it efficient and well-structured.

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 complexity (a recommendation tool with 2 parameters, no annotations, and no output schema), the description is moderately complete. It covers the purpose and some behavioral traits but lacks details on output format, error cases, or integration with sibling tools. Without an output schema, the agent is left guessing what the recommendations look like, which is a notable gap for effective tool invocation.

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 input schema has 100% description coverage, with clear documentation for both parameters ('task' and 'project_path'). The description adds minimal value beyond the schema: it implies the 'task' parameter influences recommendations but doesn't specify how, and it doesn't mention the 'project_path' at all. Since schema coverage is high, the baseline is 3, as the description doesn't significantly enhance parameter understanding.

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: 'Detect what the project needs and recommend the best tool/service for each scenario.' It specifies the verb (recommend) and resource (tools/services like auth, database, payments, deployment tools) and mentions it's based on current task and existing dependencies. However, it doesn't explicitly distinguish this from sibling tools like 'coach' or 'idea_score' that might also involve guidance or recommendations, leaving some ambiguity.

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 usage context: 'based on current task and existing dependencies' and 'Same scenario is not recommended twice,' which suggests it's for project development scenarios and avoids duplicates. However, it doesn't explicitly state when to use this tool versus alternatives like 'coach' or 'idea_score,' nor does it provide exclusions or prerequisites, leaving the agent to infer appropriate usage.

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