get_lesson_transcript

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

No annotations are provided, so the description carries the behavioral disclosure burden. It states exactly what is returned (full timestamped transcript) and that timestamps are included by default via include_timestamps parameter. It does not mention failure cases, authentication requirements, or whether the transcript is always available for every lesson item. A 3 is reasonable.

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?

Two sentences. First sentence states the purpose; second sentence provides the exact identifier format. Example values are placed inline, avoid unnecessary fluff.

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 read-only transcript fetch with an output schema present, the description is nearly complete. It explains the key identifier, the defaults and potential mitigations like timestamp control. It doesn't explicitly explain course_slug semantics, but the parameter name and the domain ('course') make that inferable. The output schema presumably carries return shape, so no extra description needed.

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 coverage is 0%, so the description must add semantic value for the parameters. It explains what lesson_slug_or_index is and provides concrete examples. course_slug is described in the schema by its name, but the description does not explicitly explain what a course_slug looks like or how to obtain it. include_timestamps is semantically clear from its name and defaults in the schema. The description adds some value for the core parameter but not full compensation.

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?

States a specific verb ('Get'), a specific resource ('full timestamped transcript for a lesson in a DeepLearning.AI course'), and gives both accepted identifiers. It clearly distinguishes itself as a lesson-level retrieval tool and differs from siblings like get_lesson_lab or search_course_content because it returns the lesson transcript.

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?

Gives clear when-to-use context: it is the tool for retrieving lesson transcripts. It also gives an explicit input convention (lesson index or slug) and an example. It does not explicitly rule out alternatives like search_course_content, but its scope is clear enough that an agent can select it.

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