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build_lesson_content

Creates EditorJS JSON content for a lesson from a provided specification including paragraphs, headers, lists, images, code, embeds, quiz references, and markdown.

Instructions

Build an EditorJS JSON content string for a lesson from a spec.

Args: content_spec: JSON string with optional keys: paragraphs, headers, lists, images, code, embeds, quiz_refs, markdown. Example: '{"paragraphs":["Hello world"],"headers":[{"text":"Intro","level":2}]}'

Returns: EditorJS JSON string ready for the content field of a Course Lesson.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
content_specYes

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 must cover behavioral traits. It explains the return type (EditorJS JSON string) and that it builds from a spec, but does not mention validation, side effects, or error handling. Still, it provides adequate transparency for a builder tool.

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?

Description is concise with a clear purpose statement followed by an Args and Returns section. Every sentence adds value, no repetition or fluff.

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?

For a tool with one parameter and an output schema, the description is mostly complete. It covers input format, output format, and example. Could mention potential limitations or error cases, but overall adequate.

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%, but description fully compensates by detailing the content_spec parameter as a JSON string with optional keys (paragraphs, headers, etc.) and providing an example. This adds significant meaning beyond the schema's type-only definition.

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 the tool builds an EditorJS JSON content string from a spec, specifying the resource (lesson content) and action (build). It distinguishes from siblings like add_paragraph_to_content, which operates at a smaller scope.

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 explains what the tool does and the input format, but does not explicitly state when to use this tool vs alternatives like add_paragraph_to_content or creating a lesson. Usage context is implied but not clearly delimited.

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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