generateLearningPath

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

With no annotations provided, the description carries the burden of behavioral disclosure. It indicates the output will contain steps, resources, and milestones, but does not explain any limitations, prerequisites (beyond schema), return format, or whether results are custom vs. templated. It adds some context but leaves significant room for ambiguity.

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, well-formed sentence that is front-loaded with the primary action and includes necessary details about the output without any filler. Every word contributes value.

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 is relatively simple with a clear schema and three enums, and the description covers the core outcome (steps, resources, milestones). Since there is no output schema, the description provides a reasonable expectation of the result. It could be slightly richer (e.g., mention that it adapts to current/goal levels), but the overall context is sufficiently complete.

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 already provides 100% coverage with descriptive text for each parameter (topic, currentLevel, goalLevel, timeCommitment). The description adds no additional parameter-level semantics, so it falls at the baseline of 3 as the schema does the heavy lifting.

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 ('Creates') and identifies a clear resource ('structured learning path') with concrete deliverables ('steps, resources, and milestones'), distinguishing it from sibling tools like explainConcept or debugHelper. The purpose is immediately obvious and unambiguous.

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 implies the tool is for generating a learning path 'for learning a topic', which gives a clear usage context. However, it does not explicitly mention when to prefer this tool over alternatives, nor does it provide exclusions or complementary use cases with sibling tools. The guidance is implied rather than stated.

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