agtask_get_model_config

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

With no annotations, the description carries the full behavioral burden; it does imply a non-mutating, agent-scoped read ('本 Agent'), which is useful context. However, it never explicitly states that the operation is read-only, whether results are cached or per-workspace, or what the response contains. For a zero-parameter getter the risk is low, so a 3 rather than a 1-2 is fair.

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 short sentence with the action and scope front-loaded and no filler. It is efficient, but its brevity is partly under-specification rather than deliberate tightening.

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 zero-parameter tool with no output schema, the description is the only source of information about what comes back, and it does not describe the shape of the returned configuration (which purposes, which fields). It is minimally adequate but leaves the agent guessing about the return value.

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 are no parameter semantics to document; the baseline of 4 applies. Nothing in the description misleads about inputs.

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 gives a specific verb and resource: it retrieves (获取) this agent's default model configuration, classified by usage (按用途分类). That is clearer than a bare name restatement, and the read nature distinguishes it from the sibling agtask_set_default_model, though the description never names that sibling or explains what the 'usage classification' actually contains.

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?

There is no when-to-use guidance, no mention of the complementary agtask_set_default_model, and no indication of when an agent should call this versus agtask_call_model or agtask_get_balance. The agent must infer the use case from the name alone.

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