get_workout_templates

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only describes the content (templates) but does not state whether reading these templates modifies anything, whether network requests are made, or how large the template list is. Since there are no params, the agent cannot know if any scoping or filtering exists.

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 a single compact sentence in Chinese, approximately 20 characters. It conveys the core purpose without fluff. For an LLM agent, the conciseness is good, though the language choice may slightly hinder readability.

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 the tool has 0 parameters and an output schema exists (providing structure for the return value), the description is adequate. It names the resource type (JSON templates) and specific plan categories. However, it does not mention that the tool is read-only, which would be helpful for behavioral clarity. The output schema covers the response format, so return value details are not needed in the description.

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 input schema has 0 parameters, and schema description coverage is 100% (there is nothing to describe). The baseline score for 0-param tools is 4 according to guidelines. The description does add context about what the templates contain (simple run, intervals, tempo, strength circuits), which is valuable beyond the empty 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 '常用训练计划 JSON 模板库（简单跑/间歇/节奏/力量循环）' indicates the tool provides JSON templates for common training plans including easy run, intervals, tempo, and strength circuits. This specifies a resource (templates) and categories, but uses a Chinese language description which may reduce clarity for English-speaking LLM agents. It distinguishes from siblings like 'get_workouts' which likely retrieve actual workout data, not templates.

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?

No explicit usage recommendations or exclusions are provided. The description does not mention when to use this tool instead of alternatives such as 'get_workouts' or 'get_activity_types'. The agent must infer usage from the resource category ('templates' vs actual data).

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