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Dalea AI

Update script preferences

update_script_preferences
DestructiveIdempotent

Update the brand's script preferences. Only the keys present in patch are replaced (a list key replaces the whole list); everything else is kept. formats must be taxonomy slugs (talking_head, voiceover_broll, listicle, tutorial, storytelling, reaction, pov, street_interview, day_in_life, podcast_clip, green_screen). defaultDurationSeconds 5-600 or null. Restrictions live elsewhere (add_restriction). Returns the full preferences document.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
patchYes
brandIdNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations declare destructiveHint=true and idempotentHint=true, and the description meaningfully complements them by spelling out the exact merge/replace semantics that determine what gets destroyed (list keys fully replaced) and by stating it returns the full preferences document despite no output schema. Strong added context beyond the 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?

Four tight sentences, front-loaded with the verb and the critical patch-merge rule, then constraints, then the routed alternative, then the return value. No filler.

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 destructive nested-patch mutation with no output schema, the description covers the highest-risk behaviors (merge vs replace, return shape) and one parameter family in detail. It leaves several nested keys unmentioned, but the schema's own constraints (maxItems, maxLength, enums) mitigate this.

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 description coverage is 0%, so the description must carry parameter meaning. It documents the formats slug values and the defaultDurationSeconds range (5-600 or null), but pillars, bannedHooks, approvedHooks, useLearnedFormats, standingInstructions, and brandId get no explanation. Partial but not full compensation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Update the brand's script preferences') and names the sibling get_script_preferences implicitly via the returned document. It does not explicitly contrast itself with siblings like add_restriction or get_script_preferences, but the operation is unambiguous.

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?

Explicitly describes the patch contract ('only the keys present in patch are replaced; a list key replaces the whole list') and routes a related capability away with 'Restrictions live elsewhere (add_restriction).' That is clear when-to-use context, though there is no explicit when-not-to-use statement.

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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