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start_course_build

Initiate a course build pipeline: creates a course record and returns an intake questionnaire for specifying topic, audience, duration, and notes.

Instructions

Start a new course build pipeline.

Creates a course record in the course_builds table, adds a placeholder
row to learning_courses (status='building'), and returns the intake
questionnaire for the user to complete.

Args:
    topic: The subject or title of the course (e.g. "Multilevel models for epidemiologists")
    target_audience: Who this course is for (e.g. "MPH students with basic R knowledge")
    duration_hours: Estimated total course length in hours (0 = TBD)
    notes: Any initial notes or constraints the user has mentioned

Returns:
    Course ID, a brief confirmation, and the intake questionnaire.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYes
target_audienceNo
duration_hoursNo
notesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries full responsibility. It discloses that the tool creates records and returns a questionnaire, but doesn't discuss side effects, permissions, or error conditions. However, it is transparent about the core behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with a clear structure: brief summary, then detailed explanation of args and returns. Every sentence adds value; no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity and lack of schema descriptions, the description covers the essential aspects: what it does, the arguments, and the return value. It is complete enough for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description includes an Args section that explains each parameter's purpose, especially clarifying duration_hours (0 = TBD) and notes. This adds meaning beyond the bare schema, which has no descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('start'), the resource ('course build pipeline'), and provides a detailed breakdown of what it does (create record, add placeholder, return questionnaire). It distinguishes from sibling tools like get_course_status or save_course_curriculum.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide explicit guidance on when to use this tool versus alternatives. It assumes the agent knows to start a new build, but doesn't mention prerequisites, conflicts with existing builds, or when not to use it.

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

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