glm_cancel

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

With no annotations provided, the description fully carries the burden of behavioral disclosure. It explicitly states that the harness has no mid-turn cancel, that the child process is killed, that in-flight runs are reported as cancelled, that file edits persist, and that the session context cannot be resumed. This is exemplary transparency for a destructive 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?

The description is tightly structured: a one-sentence purpose statement, a short behavioral detail block, and an args section. There is no filler or redundancy—each sentence adds essential information about what the tool does or what the agent should do afterward.

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 description covers all key aspects of this session-ending operation: mechanism, effect on in-flight work, persistence of file edits, and the inability to resume. With an output schema present and a single parameter, no significant information is missing for an agent to decide whether and how to invoke the tool.

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 0%, so the description must compensate. The Args section ('agent_id: Agent to stop') gives the parameter a clear role and connects it to the tool's purpose. For a single parameter, this is sufficient, though it could have added where to find the ID (e.g., via glm_list).

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: 'Stop a subagent and release its runtime process.' It clearly distinguishes this from siblings like glm_delegate and glm_await, which handle creation and waiting, and even explains the mechanism (killing the child process) that makes this tool unique.

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 the tool: when a subagent must be stopped and its runtime process released. It also provides critical post-cancel guidance—'start a new agent rather than continuing this one'—which prevents misuse. It does not explicitly name alternative tools, but the sibling set and the cancellation semantics make the use case obvious.

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