rlm_multi_project_query

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

With no annotations, the description must disclose behavioral traits. It indicates a query operation but lacks details on side effects, rate limits, authentication beyond the key, or return behavior. The description does not add value beyond the basic purpose.

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 brief and front-loaded, consisting of two concise sentences. Every word contributes to the core purpose. However, it sacrifices informativeness for brevity.

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 8 parameters, no output schema, and the complexity of cross-project querying, the description is severely incomplete. It does not explain return format, pagination, or behavior across projects, leaving significant 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?

Schema description coverage is only 38%, and the description provides no information about parameters. The agent must rely on sparse schema descriptions, which only cover two out of eight parameters. The description fails to add meaning or guidance for parameter usage.

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 queries across all projects in a team, providing a specific verb and resource. It also notes the requirement for a team API key, adding context. However, it does not explicitly differentiate from similar sibling tools like rlm_search or rlm_multi_query.

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 only mentions the requirement for a team API key, offering minimal guidance on when to use this tool versus alternatives. No exclusion criteria or specific use cases are provided, leaving the agent to infer appropriateness.

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