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save_course_outline

Save an approved course outline to advance the course build to Step 3 (Harvest).

Instructions

Save an approved course outline after Step 2 (Scope Plan).

Call this once the user has reviewed and approved the module outline.
Pass outline_json as a JSON array of module objects:
  [{"module": 1, "title": "...", "bloom_level": "...", "hours": 2}, ...]

Args:
    slug: The course slug returned by start_course_build()
    outline_json: JSON array of module definitions
    approved: Must be True to advance the build to Step 3 (Harvest)

Returns:
    Confirmation and next-step instructions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes
outline_jsonYes
approvedNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries full burden. It discloses the action, required input format, and conditional advancement, but lacks details on side effects, error behavior, idempotency, or permission requirements. Some information is provided but not comprehensive.

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 no fluff. The main purpose is front-loaded, followed by a structured breakdown of arguments and returns. Every sentence earns its place.

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 an output schema exists, the description covers essential context: workflow position, input format, and conditional behavior. It does not address validation or error handling, but for a save tool in a pipeline, it is mostly complete.

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

Parameters5/5

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

Schema description coverage is 0%, but the description adds significant meaning: for outline_json it gives a detailed JSON example, for slug it specifies the source (start_course_build()), and for approved it explains the consequence (advances to Step 3). This goes well beyond the schema's titles and types.

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 states 'Save an approved course outline after Step 2 (Scope Plan)', clearly identifying the verb and resource. It distinguishes from sibling tools like save_course_curriculum by specifying its role in the course build workflow and that it advances to Step 3.

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

Usage Guidelines4/5

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

The description explicitly says 'Call this once the user has reviewed and approved the module outline' and notes that 'approved: Must be True to advance the build to Step 3'. It provides clear context but does not explicitly list alternatives or when not to use.

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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