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review_course

Run quality checks on a drafted course, validating lesson files, headers, content length, and JSON integrity. Fix failures before publishing to ensure course completeness.

Instructions

Step 6 — Run quality checks on a drafted course before publishing.

Checks:
  - All lessons in lessons.json have a corresponding file on disk
  - Each lesson file contains the required section headers
  - No lessons are empty (< 200 chars)
  - lessons.json is valid JSON with modules and lessons arrays

Returns a pass/fail report. Fix any failures before calling publish_course().

Args:
    slug: The course slug to review.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations provided, so description carries full burden. Clearly states it runs checks and returns a pass/fail report. Implies non-destructive but doesn't explicitly confirm no side effects. Still clear and sufficient.

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?

Well-structured with bullet points listing checks, a result note, and args section. No fluff, every sentence adds value.

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

Completeness5/5

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

Given the output schema exists, the description covers all needed context: what checks are performed, what the tool returns, and how it fits into the workflow (before publish). Complete for a validation tool.

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?

Single parameter 'slug' described as 'The course slug to review.' Adds meaning beyond schema by specifying it's a course slug and purpose (to review). Adequate for a simple parameter.

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?

Description clearly states 'Run quality checks on a drafted course before publishing' with a specific verb and resource. Lists concrete checks, distinguishing it from siblings like publish_course.

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

Usage Guidelines5/5

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

Explicitly states when to use (before publishing) and what to do after (fix failures before calling publish_course()). No ambiguity.

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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