rlm_htask_complete

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

With no annotations, the description carries the full burden. It discloses that evidence may be required, that memory creation is automatic unless disabled, and what the memory contains (outcome, learnings, decision impact). It could further detail side effects for non-leaf tasks or completion status, but it is largely transparent.

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 three sentences, front-loaded with the core action, and each sentence adds distinct information (purpose, usage, behavioral effect). No redundant or filler content; it is optimally concise.

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 no output schema, so the description should indicate what is returned. It does not mention return values, status, or errors. It covers the behavior (memory creation) but omits the completion result, making it slightly incomplete for an agent to anticipate outcomes.

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 coverage is 100%, so baseline is 3. The description adds value by explaining that evidence may be policy-required and that memory creation is automatic, which goes beyond the schema. This enriches the agent's understanding of the parameters' roles.

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 action ('Complete an N3 task') and the resource ('leaf tasks (N3_TASK)'). It distinguishes from sibling tools like 'rlm_task_complete' by specifying it's for hierarchical tasks. The inclusion of 'evidence' and 'optional memory creation' further clarifies the tool's scope.

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 advises using this tool for leaf tasks (N3_TASK) and mentions that evidence may be required by policy. However, it does not explicitly state when to avoid this tool or name alternative tools (e.g., 'rlm_htask_close' or 'rlm_task_complete'), leaving some ambiguity.

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