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save_course_sources

Save harvested source metadata for a course by passing a JSON array of source objects. Each source is written as a YAML file, advancing the build to the next step.

Instructions

Step 3 — Save harvested source metadata for a course.

Call this after the Content Harvester has collected materials. Pass a
JSON array of source objects. Each source is written as a YAML file in
`knowledge/courses/{slug}/sources/` and the build advances to Step 4.

Args:
    slug: The course slug.
    sources: JSON array of source dicts — each must have at least a
             ``title`` and one of ``url``, ``file_path``, or ``doi``.
             Example: '[{"title": "OpenIntro Stats", "url": "https://openintro.org/book/os/", "type": "textbook"}]'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes
sourcesYes

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 the full burden. It discloses that source files are written as YAML in a specific path and the build advances, but does not mention overwrite behavior, validation, required permissions, or error handling. This provides some but not comprehensive behavioral insight.

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 (~100 words), well-structured with a header, usage note, and argument list. Every sentence serves a purpose with no redundancy.

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?

The description covers the step context, input requirements, and action. Although an output schema exists, the description does not mention return values, which is acceptable per guidelines. It lacks any mention of error conditions or side effects but is still fairly complete for a simple tool.

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 coverage is 0%, so description is essential. It defines both 'slug' and 'sources', includes required fields for each source dict ('title' plus one of url/file_path/doi'), and provides an example. This adds high value beyond the schema.

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 verb 'Save', the resource 'harvested source metadata', and the context 'for a course'. It positions it as Step 3 in a build process, distinguishing it from sibling tools like save_course_curriculum or save_course_outline.

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?

It explicitly says to call this after the Content Harvester has collected materials and that it advances to Step 4. While it does not list negative cases or alternatives, the step context provides clear usage guidance.

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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