get_learning_plan

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

No annotations are provided, so the description carries the full burden. It conveys the core behavior: generating a personalized, stage-based calligraphy learning plan. However, it does not disclose whether the plan is persisted, what exact output format to expect, or any limitations of the generation, leaving some operational behavior unexplained.

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 two short, focused sentences with no filler. The first sentence states the main action and object, and the second clarifies inputs and what the user receives. It is appropriately sized and front-loaded.

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 simple tool with three optional, well-documented parameters and no output schema, the description covers the purpose, input basis, and the high-level output (stage-by-stage suggestions). It could be more explicit about the plan's structure or content, but the essentials are present 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 100%, so the schema already documents all three parameters fully. The description adds no new parameter semantics; it mentions goal and current_level but omits daily_minutes. It therefore meets the baseline but provides no extra value beyond 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 uses a specific verb, 制定 (formulate/create), and names the resource, 个性化的书法学习计划 (personalized calligraphy learning plan), while also stating the basis (current level, goal) and output (stage-by-stage suggestions). This clearly distinguishes it from sibling info-retrieval tools such as get_technique_guide or get_master_info.

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 provides no explicit guidance about when to use this tool versus alternatives, nor does it mention any exclusions or routing conditions. It implies use when a user needs a learning plan, but it does not help an agent choose between this and related tools like get_technique_guide or get_aesthetic_insight.

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