glm_await

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

With no annotations present, the description carries the full behavioral burden and does so well: it discloses blocking semantics, timeout behavior (returns current state rather than error), repeat-call safety, and that archived runs remain readable after reaping. These details are not visible in the schema or annotations.

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 compact and front-loaded with the core purpose, followed by behavior notes and a structured Args section. Every sentence adds operational value with no filler or repetition of the schema.

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 two-parameter polling tool with an output schema, the description covers the essential operational context: when to call it, what it does when the run is unfinished, repeat safety, and persistence of results. Nothing an agent needs to decide whether to invoke it correctly 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 0%, so the description must explain parameters, and it does: run_id is defined as the run to wait on with explicit provenance, and wait_seconds is explained as the maximum block time with sizing guidance for big tasks. This adds meaning well beyond the bare schema.

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 leads with a specific verb and resource: 'Wait for a run to finish and return its result.' This clearly distinguishes glm_await from sibling tools like glm_list, glm_cancel, and glm_transcript, and the run_id provenance from glm_delegate/glm_continue makes its role in the workflow explicit.

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?

It gives clear context for when to use the tool: after obtaining a run_id from glm_delegate or glm_continue, to block until completion. It also states that repeated calls are safe, which is useful polling guidance, though it does not explicitly name alternatives or state when not to use it.

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