glm_transcript

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

With no annotations, the description carries the full burden and does so well. It reveals that data is live while the run is ongoing, that only the tail is returned by default, and that raw returns an uncapped response. It implies a read-only inspection operation through wording like 'show' and 'returns.' Minor omissions like error behavior or pagination, but the core behavioral traits are disclosed.

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 summary sentence is front-loaded and concise. The subsequent detail paragraph and args list are clearly structured with no fluff. Every sentence adds useful information, and the format is easy to scan.

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 tool has an output schema, so return-value details need not be repeated. The description covers the essential context: what the log contains, live behavior, the limit mechanism, and the raw option. Missing explicit failure semantics or auth requirements, but for a read-only inspection tool the provided information is complete enough for 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 0%, so the description fully compensates. It explains run_id as 'the run to inspect,' limit as the number of recent activity lines, and raw with a detailed rationale tying it to glm_delegate's distillation behavior. This adds meaning far beyond the bare type/default information in the 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 opens with a specific verb and resource: 'Show what a subagent actually did during a run.' It clearly states the tool returns the tail of an activity log (tool calls, assistant messages, turn endings), distinguishing it from siblings like glm_delegate or glm_await. The raw parameter explicitly contrasts with glm_delegate's distilled version, further differentiating it.

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 concrete use cases: 'check progress on a long run, or to understand a failure.' It also explains when the raw parameter matters relative to glm_delegate's output. It does not explicitly say when not to use this tool or name sibling alternatives, but the provided context is enough to guide selection.

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