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run creative chain

run_creative_chain
Idempotent

run creative chain. Classification: writes to Studio, creates billable AI usage. Execution: durable. Task support: optional. Mutation modes: validate_only, preview_only, execute. Partial failure policy: completed_items_not_rolled_back. The returned JSON is internal application state for LeanrIQ and ChatGPT orchestration. Use assistantSummary first when responding to the user. Never display raw JSON, data, or meta unless the user explicitly asks for raw JSON. Mention IDs only when useful for follow-up or debugging. Prefer concise, human language, highlight the most useful insight, and suggest the next best LeanrIQ action. If idempotencyKey is omitted on a mutation, the MCP layer derives a deterministic retry key from the tool and business arguments so an accidental identical replay cannot create duplicate work. For a mutation when more than one seat is authorised, seatId or seatName must be supplied on that exact tool call; a remembered or previously selected seat is not sufficient for a write.

Input Schema

NameRequiredDescriptionDefault
KPINo
goalNo
toneNo
brandNo
forceNo
offerNo
budgetNo
seatIdNo
channelNo
endDateNo
productNo
audienceNo
buildAdsNo
seatNameNo
accountIdNo
mustAvoidNo
objectiveNo
startDateNo
campaignIdNo
creativeIdNo
constraintsNo
creativeIdsNo
funnelStageNo
mustIncludeNo
targetSizesNo
advertiserIdNo
campaignNameNo
deliverablesNo
saveToStudioNo
sourceLocaleNo
targetMarketNo
contentLocaleNo
marketContextNo
targetMarketsNo
contentLocalesNo
idempotencyKeyNo
defaultContentLocaleNo
marketLanguageProfileNo
resolvedContentLocaleNo
languageVariantGroupIdNo
requestedOutputLocalesNo
supportedContentLocalesNo

Output Schema

NameRequiredDescriptionDefault
dataYes
metaYes
errorNo
statusYes
assistantSummaryYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed12 schema fields changed
    • addedInput schema / properties / contentLocale
      Added value: +{
      +  "type": "string"
      +}
    • addedInput schema / properties / contentLocales
      Added value: +{
      +  "items": {
      +    "type": "string"
      +  },
      +  "maxItems": 20,
      +  "type": "array"
      +}
    • addedInput schema / properties / defaultContentLocale
      Added value: +{
      +  "type": "string"
      +}
    • addedInput schema / properties / languageVariantGroupId
      Added value: +{
      +  "maxLength": 160,
      +  "minLength": 1,
      +  "type": "string"
      +}
    • addedInput schema / properties / marketContext
      Added value: +{
      +  "properties": {
      +    "currency": {
      +      "anyOf": [
      +        {
      +          "type": "string"
      +        },
      +        {
      +          "type": "null"
      +        }
      +      ]
      +    },
      +    "targetMarket": {
      +      "anyOf": [
      +        {
      +          "type": "string"
      +        },
      +        {
      +          "type": "null"
      +        }
      +      ]
      +    },
      +    "targetMarkets": {
      +      "items": {
      +        "type": "string"
      +      },
      +      "type": "array"
      +    },
      +    "timeZone": {
      +      "anyOf": [
      +        {
      +          "type": "string"
      +        },
      +        {
      +          "type": "null"
      +        }
      +      ]
      +    }
      +  },
      +  "type": "object"
      +}
    • addedInput schema / properties / marketLanguageProfile
      Added value: +{
      +  "additionalProperties": {},
      +  "propertyNames": {
      +    "type": "string"
      +  },
      +  "type": "object"
      +}
    • addedInput schema / properties / requestedOutputLocales
      Added value: +{
      +  "items": {
      +    "type": "string"
      +  },
      +  "maxItems": 20,
      +  "type": "array"
      +}
    • addedInput schema / properties / resolvedContentLocale
      Added value: +{
      +  "type": "string"
      +}
    • addedInput schema / properties / sourceLocale
      Added value: +{
      +  "type": "string"
      +}
    • addedInput schema / properties / supportedContentLocales
      Added value: +{
      +  "items": {
      +    "type": "string"
      +  },
      +  "maxItems": 20,
      +  "type": "array"
      +}
    • addedInput schema / properties / targetMarket
      Added value: +{
      +  "maxLength": 160,
      +  "minLength": 1,
      +  "type": "string"
      +}
    • addedInput schema / properties / targetMarkets
      Added value: +{
      +  "items": {
      +    "maxLength": 160,
      +    "minLength": 1,
      +    "type": "string"
      +  },
      +  "maxItems": 50,
      +  "type": "array"
      +}
  2. First observed

TDQS

B3.2/5.0
Behavior5/5

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

Annotations already cover readOnlyHint=false, idempotentHint=true, destructiveHint=false, but the description goes well beyond them: billable AI usage, durable execution, optional task support, the partial-failure policy (completed_items_not_rolled_back), deterministic idempotency-key derivation on replay, and the multi-seat write requirement. This is unusually rich behavioral disclosure with no contradiction of 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.

Conciseness3/5

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

The labeled structure (Classification, Execution, Task support, Mutation modes, Partial failure policy) is front-loaded and scannable, but the first sentence is pure waste and the four-sentence response-formatting paragraph is largely generic boilerplate for an agent-facing tool. Net length is defensible but not tight.

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

Completeness2/5

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

Output schema exists, so return values need not be described (the description covers response handling anyway). However, for a 42-parameter, zero-coverage, nested-object mutation tool, the near-total absence of input parameter guidance is a serious completeness gap. Annotations cover the safety profile but not the calling contract.

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

Parameters2/5

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

42 parameters at 0% schema description coverage means the description carries the full burden, yet it only explains idempotencyKey and seatId/seatName semantics. The core inputs (KPI, goal, tone, brand, offer, budget, audience, deliverables, locale/market fields) are entirely undefined in both schema and description, leaving most of the surface opaque.

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

Purpose3/5

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

The opening sentence 'run creative chain' is a tautological restatement of the name and never explains what a 'creative chain' actually is. The 'Classification' line adds real substance (writes to Studio, creates billable AI usage), but the description never distinguishes this tool from near-neighbors like launch_creative_campaign or run_creative_intelligence. Purpose is implied rather than stated.

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?

It supplies conditional invocation guidance — mutation modes (validate_only, preview_only, execute) and the rule that seatId/seatName must be passed on the exact call when more than one seat is authorised — but none of these map to a parameter in the schema and there is no explicit statement of when to choose this tool over its siblings. Usage is implied, not directed.

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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