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traffick flight

traffick_flight
Idempotent

traffick flight. Classification: publishes externally. 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
forceNo
dryRunNo
seatIdNo
flightIdYes
seatNameNo
accountIdYes
approvalIdNo
creativeIdNo
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

B3.1/5.0
Behavior4/5

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

Beyond the annotations (mutation, open-world, idempotent, non-destructive), the description adds real operational detail: durable execution, optional task support, a partial-failure policy of 'completed_items_not_rolled_back', deterministic idempotency-key derivation on replay, and the requirement to pass seatId/seatName on the exact mutation call when multiple seats are authorized. These are non-obvious behaviors an agent could not infer from structured fields alone.

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 metadata fields are front-loaded and readable, but the description mixes tool behavior with ChatGPT presentation instructions ('Never display raw JSON... suggest the next best LeanrIQ action'), which is verbose boilerplate relative to the tool's own contract. For a 21-param mutation some length is justified, but several sentences do not describe the tool itself.

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?

An output schema exists, so return values needn't be explained, and the description does cover idempotency, seat authorization, partial-failure handling, and mutation modes. However, it leaves the core purpose of 'trafficking' and nearly all of the 21 parameters unexplained, so an agent has behavioral context but not enough to invoke the tool confidently.

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?

With 21 parameters and 0% schema description coverage, the description carries the full burden but explains only idempotencyKey (auto-derivation) and seatId/seatName (must be supplied on the write). The remaining ~18 parameters - flightId, creativeId, approvalId, locale/market fields, marketContext, force, dryRun, etc. - get no meaning, format, or constraint explanation.

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 description opens by restating the tool name ('traffick flight') and only obliquely conveys the action via 'Classification: publishes externally'. That hints at publishing the flight externally, but the purpose is buried in metadata fields rather than stated as a clear verb+resource. It does not distinguish itself from close siblings such as validate_flight, preview_trafficking_output, retraffick_flight, or push_flight_to_yahoo.

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?

Usage is implied through 'Mutation modes: validate_only, preview_only, execute' and the seat prerequisite, but the description never says when to choose this tool over validate_flight, preview_trafficking_output, or retraffick_flight. The bulk of the text is assistant-response guidance rather than tool-selection guidance, so the agent must infer the right context.

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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