create_course_outline

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

No annotations are provided, so the description must cover behavioral traits. It lists what the tool returns but does not disclose how it generates the outline (e.g., AI model used, limitations, or any side effects). The output description is useful but not comprehensive for behavioral transparency.

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 sentences with no unnecessary words. It front-loads the core purpose and lists output components efficiently. Every sentence earns its place.

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 an output schema, the description need not elaborate on return values. It already covers the key output items. With good schema coverage and no nested objects, the description is complete for this moderately complex tool.

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 100% coverage, so the baseline is 3. The description adds no new meaning beyond restating that the tool works for any topic and audience level, which is already implied by the parameter descriptions. No additional semantics provided.

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 generates a detailed, structured course outline and lists specific output components (modules, lessons, objectives, durations, assessment ideas). It distinguishes itself from sibling tools like analyze_course_feedback or batch_generate_reports which perform different tasks.

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 can be used for any topic and audience level, but does not explicitly state when to use it over alternatives or provide exclusion criteria. Sibling tools are sufficiently different, so no guidance is needed for distinguishing, but lack of explicit usage context lowers the score.

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