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contentrain_model_save

Idempotent

Create or update content model definitions, auto-committing changes to Git to keep content structure version-controlled.

Instructions

Create or update a model definition. Changes are auto-committed to git — do NOT manually edit .contentrain/ files after calling this tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesModel ID (kebab-case, e.g. "blog-post")
i18nYesWhether this model supports localization
kindYesModel kind
nameYesHuman-readable name
domainYesContent domain (e.g. "blog", "marketing", "system")
fieldsNoField definitions (not needed for dictionary)
descriptionNoModel description
title_fieldYesName of the field shown as an entry's title in listings, pickers and relation references. Must name a field on this model whose type is string, text, slug, email, url, code, markdown or richtext. Dictionary models have no fields — use "key".
content_pathNoFramework-relative path for content files (e.g. "content/blog", "locales"). When set, content is written here instead of .contentrain/content/
locale_strategyNoHow locale is encoded in file names. Default: "file"
Behavior4/5

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

The description discloses a key behavioral trait beyond annotations: changes are auto-committed to git, and warns against manual edits after calling. While annotations already indicate this is a write operation (readOnlyHint=false), the git side effect is valuable additional context not captured by annotations.

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 two sentences, front-loaded with the primary action, and every word serves a purpose. The critical git auto-commit warning is efficiently integrated without redundancy.

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

Completeness3/5

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

The tool is complex with 10 parameters and nested objects, but the schema is very detailed, covering parameter semantics. The description lacks information about return values, validation behavior, or how create vs. update is determined, but the schema and annotations provide much context. Still, for a tool with no output schema and this complexity, a bit more behavioral context would improve completeness.

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

Parameters3/5

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

Schema documentation coverage is 100%, so the schema carries full parameter semantics. The description adds no additional parameter meaning, which is acceptable given the high schema coverage, but it does not enhance or clarify any parameter details.

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 'Create or update a model definition' with a specific verb and resource. This distinguishes it from sibling tools like contentrain_model_delete and contentrain_content_save, which target different objects or operations.

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 implies usage (for creating/updating model definitions) and includes a post-action warning about not manually editing .contentrain/ files. However, it does not explicitly mention when to use this tool versus alternatives or state any exclusions, so it falls short of 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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