Поставити задачу GLM

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

With no annotations, the description carries the full burden. It discloses that it waits by default and returns run_id immediately with background:true, and notes the prompt must be prepared with prompt-master. However, it omits other behaviors like token consumption, error handling, or whether the operation is destructive.

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 short and front-loaded, stating the core purpose and the key constraint first. Every sentence adds relevant information, and it avoids redundancy.

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?

Given 14 parameters and no annotations or output schema, the description is insufficient. It doesn't describe the return format (other than run_id for background), error handling, or how to retrieve results later. The tool is complex, and the description leaves many operational gaps.

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 coverage is 100%, so the schema already documents all parameters. The description adds some context (e.g., the prompt requirement, background behavior) but doesn't significantly go beyond the schema's own descriptions. It meets the baseline but adds little extra value.

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 clearly states the tool executes a ready prompt, using a specific verb and resource. It differentiates from siblings like glm_build_prompt by emphasizing the prompt must already be composed, but it doesn't explicitly name alternative tools.

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 provides context on when to use it (with a ready prompt composed via prompt-master skill) and mentions a fallback via refine, but it doesn't explicitly list alternative tools or state when not to use it. The guidance is implicit rather than explicit.

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