rlm_htask_recommend_batch

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

No annotations; description does not disclose potential side effects, authorization needs, or rate limits beyond being a read operation.

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?

Two concise sentences with no fluff; front-loads purpose and adds filtering guidance.

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?

Explains return type (prioritized list) but omits format details; no output schema, so more detail on list contents would help.

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 covers all parameters; description adds context like 'prioritized', 'unblocked', and 'pending', but not significantly beyond 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 tool returns a recommended batch of N3 tasks, prioritized and unblocked, distinguishing it from sibling list/create tools.

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?

Mentions optional filters but lacks explicit guidance on when to use this vs. alternatives like rlm_task_list or rlm_htask_get.

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