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Save my AI’s text variations

studio_copy_save
Idempotent

Saves finished customer-authored headline/caption drafts and supporting source facts as a free text version. Identical source/revision/result inputs return the saved version. No Brix36 language-model request, publishing or credit charge.

Input Schema

NameRequiredDescriptionDefault
resultYes
projectIdYesThe current owned project.
sourceTextYesExact customer-supplied source facts supporting the draft.
finishedAssetIdNoOptional completed master the text accompanies.
expectedRevisionYesCurrent project revision. A stale revision returns revision_conflict.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare idempotentHint=true, destructiveHint=false and readOnlyHint=false; the description usefully reinforces idempotency semantics ('identical source/revision/result inputs return the saved version') and adds non-obvious traits not in annotations — no LLM call, no publishing, no credit charge. It doesn't describe what a successful response returns, but that is largely covered by the output schema.

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?

Two dense sentences, front-loaded with the core action and followed by the behavioral guarantees. Every clause earns its place — the cost/publishing/LLM disclaimer is exactly what an agent needs to avoid a wrong tool choice.

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?

With an output schema present and annotations covering the safety profile, the description covers the essentials: what is saved, idempotency, and the absence of cost or publishing side effects. Minor gaps remain — it never mentions the optional finishedAssetId linkage or what a stale expectedRevision produces — but the schema carries the latter.

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 coverage is 80%, so the schema already documents projectId, sourceText, finishedAssetId and expectedRevision. The description only echoes 'source/revision/result' in the idempotency sentence and adds no syntax, format, or constraint detail beyond the schema, so baseline 3 applies.

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?

States a specific verb and resource — 'Saves finished customer-authored headline/caption drafts and supporting source facts as a free text version' — which is immediately distinguishable from the read-side sibling studio_copy_read and from generation tools. An agent knows exactly what artifact this persists 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 Guidelines4/5

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

It gives clear context for choosing this tool: the operation makes no language-model request, does no publishing, and incurs no credit charge, so an agent can tell it apart from paid generation/confirm tools. It does not explicitly name alternatives or state prerequisites (e.g., needing an existing project), so it stops short of full when/when-not 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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