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create_author

Create a new Author record with required name and email, optionally adding inline rows. Invalid or non-editable fields are rejected, not ignored.

Instructions

Create a new Author, optionally with inline rows.

Date and datetime fields take a single ISO 8601 string (e.g. '2026-03-01' or '2026-03-01T09:30:00Z'). Foreign keys take the related object's ID, many-to-many fields a list of IDs. A field the admin form does not accept (unknown, read-only or non-editable) is rejected with an error, never ignored.

Fields:

  • articles (ForeignKey)

  • id (BigAutoField)

  • name (CharField) [required]

  • email (CharField) [required]

  • bio (TextField)

  • created_at (DateTimeField)

Input Schema

NameRequiredDescriptionDefault
dataYesThe data for the new Author
inlinesNoInline rows to create with the object, keyed by inline model name: {model_name: [{data}, ...]}. All-or-nothing: any inline error rejects the whole call and nothing is saved

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It does add genuine behavioral detail: unknown/read-only/non-editable fields are 'rejected with an error, never ignored'. But for a mutation tool it omits what happens on success (returned object/nested structure), permission requirements, and how FK/m2m side effects are applied.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded and the format rules follow logically from general to specific. The field enumeration is long but each entry carries distinct information; only slight redundancy exists between the inline-rows mention and the schema's inline description.

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 create tool with no output schema, the description adequately covers data shape, field formats, required fields, inline all-or-nothing semantics, and rejection behavior. It falls short only on success response shape and permission/authentication expectations.

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?

Schema description coverage is 100%, so the baseline is 3, but the description substantially exceeds that by enumerating all six fields with types and required markers, and by specifying ISO 8601 formats for date/datetime and ID-based conventions for FK and m2m fields. These are semantics the schema's bare 'data' object does not supply, though some fields (e.g. articles) lack clarity on whether they are writable.

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 opening sentence states a specific verb+resource combination ('Create a new Author'), which is unambiguously distinct from the surrounding CRUD siblings (get_author, update_author, delete_author, list_author). An agent can select this without opening the schema.

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 phrase 'optionally with inline rows' implies the create-with-nested-records use case, and the field-validation sentence tells the agent what input is accepted. However, there is no explicit when-to-use guidance, no direction to update_author for modifications, and no mention of prerequisites such as authentication or permissions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.