stop_learning_batch

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

No annotations are provided, so the description carries the full burden. It usefully discloses two behavioral traits – the browser stays open and pending submissions are allowed to finish – but says nothing about idempotency, whether new dispatches are blocked until resume, or what state the batch is left in.

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?

A single front-loaded sentence with no filler, and the most important constraint ('without closing the browser') is placed immediately after the verb. It is on the terse side for a stop operation but nothing is wasted.

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?

With no annotations, no output schema and no parameters, the description is the only source of behavioral detail, and it omits the post-stop state and the recovery path (resume_learning_batch). Adequate to call safely, incomplete for understanding consequences.

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?

The tool takes zero parameters, so there is no parameter semantics to explain and the baseline of 4 applies. The description correctly avoids inventing parameter discussion.

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 ('stop') and resource ('queue dispatch'), and the qualifier 'without closing the browser' distinguishes it from the browser-teardown siblings like stop_course_browser. It never names a sibling directly, keeping it just below the top score.

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?

Usage is implied by the name and the 'without ... interrupting pending submissions' hint, but there is no explicit statement of when to choose this over stop_course_browser, resume_learning_batch, or defer_current_learning_task. The agent must infer the boundary from sibling names alone.

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