rlm_plan

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

No annotations are provided, so the description must disclose behavioral traits. It states that the tool 'returns steps for decomposition, context queries, and synthesis,' but does not explain whether the operation is read-only, destructive, or any side effects. Given the absence of annotations, this minimal description is insufficient.

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 two sentences long, front-loading the purpose and output. Every word adds value with no redundancy or fluff.

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?

The tool has three parameters and no output schema. The description explains the tool's output conceptually but omits details about the format of steps, differences between strategies, or constraints like max_tokens. It is adequate for basic understanding but not fully complete.

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 67% (query and strategy have descriptions, max_tokens does not). The description adds no parameter information, such as how strategy options affect the plan or what max_tokens controls. It fails to provide 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 'Generate full execution plan for complex questions' with specific verb (Generate) and resource (full execution plan). It distinguishes from siblings like rlm_decompose by mentioning decomposition, context queries, and synthesis, indicating a higher-level planning role.

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 says 'for complex questions' but provides no explicit guidance on when to use this tool versus alternatives like rlm_decompose or rlm_orchestrate. There is no mention of when not to use it or what alternatives exist.

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