batch_start_tasks

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

With no annotations, the description carries the full behavioral burden. It does disclose useful side effects: it sets tasks to IN_PROGRESS / PROCESSING and returns compact results. However, it does not explain partial-failure behavior, whether the batch is atomic, what happens if a task cannot be started, or what 'compact results' actually contains.

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?

Three short sentences, each adding distinct value: the action, the state effect, and the efficiency comparison with the single-task sibling. There is no filler or repetition, and the most important purpose is front-loaded.

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 low-complexity tool with fully documented parameters, the description is nearly sufficient: an agent knows what to pass, what state change occurs, and that results are compact. The main gaps are the unspecified result shape and batch failure semantics, which matter because there is no output schema and no annotations, but they do not block a correct invocation.

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 the schema already documents all three parameters and their meanings. The description adds no parameter-level detail beyond 'multiple AI tasks', which maps to taskNumbers but not to teamId or projectId. The baseline of 3 is appropriate because the schema does the heavy lifting.

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 opens with a specific verb and resource: 'Start multiple AI tasks at once.' It then clarifies the effect by stating statuses are set to IN_PROGRESS / PROCESSING and distinguishes itself from start_task by explicitly framing itself as a batch alternative. An agent can clearly tell this from its siblings even before inspecting the schema.

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 gives clear context for when to use it—starting multiple tasks together—and names the alternative directly with 'More efficient than calling start_task multiple times.' It does not explicitly state when not to use it, but the batch-vs-single contrast provides adequate routing guidance.

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