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

Goes well beyond the annotations by disclosing the exact side effect (a PENDING AISuggestion row), where a human reviews it (Suggestions inbox), and the required agent behavior (poll the suggestion id until status flips to ACCEPTED). This is rich workflow context the annotations cannot convey.

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?

Four tightly packed sentences with the core action front-loaded, then side effect, then required follow-up, then the triggering condition. Every sentence carries distinct information and none is redundant.

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?

For a mutation tool with no output schema, the description supplies everything an agent needs: the artifact created, who reviews it, how to detect acceptance, and what to call next. Nothing critical is missing.

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 100%, so taskId, children, and rationale are already fully documented in the schema. The description restates the 2–10 child constraint and the 'existing/visible' task notion but adds no format or edge-case detail beyond the schema, so the baseline 3 applies.

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?

States a specific verb+resource ('propose splitting an existing task into 2–10 smaller children') and immediately clarifies the output artifact (a PENDING AISuggestion row). It also distinguishes itself from the sibling add_subtasks, which performs materialization rather than the proposal.

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?

Explicitly states when to use it ('when the brief reveals a task is too coarse to execute as one unit and you want explicit human approval before fragmenting the plan') and names the follow-up tool (add_subtasks) needed to act on an accepted suggestion. Nothing is left implicit.

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