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AdsAgent — TikTok Ads MCP

List ad creation history

tasks_list_create_history
Read-only

List recent TikTok create task history for the current user. Use this before comparing two launches such as '16号 cardyes 和昨天 targeting 有什么不同'. Returns public task summaries plus creation_snapshot_summary; it does NOT call TikTok live APIs.

REQUIRED: none. Optional: status (terminal status filter), days (1..365, default 30), search (campaign/adgroup/ad/id substring), limit (1..50, default 20). EXAMPLE: tasks_list_create_history({"search": "cardyes", "days": 14, "limit": 5})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
limitNo
searchNo
statusNo
connection_contextNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / connection_context
      Added value: +{
      +  "pattern": "^mctx_v1_[0-9a-f]{64}$",
      +  "type": "string"
      +}
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true, destructiveHint=false, openWorldHint=false, so the safety profile is free. The description adds real behavioral value on top: it returns 'public task summaries plus creation_snapshot_summary' and explicitly does not hit the live TikTok API, implying snapshot/cached data with possible staleness. Pagination behavior is the one notable omission.

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?

Front-loaded purpose, then the when-to-use rationale, then a compact REQUIRED/optional parameter summary, then a callable example — zero filler sentences and nothing redundant, since the schema documents none of the parameters.

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 no output schema, the description does sketch the return shape (task summaries + creation_snapshot_summary), which is the key completeness risk for a list tool. It leaves pagination/ordering semantics unstated, but for a non-destructive, no-required-param read tool this is close to sufficient.

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 0%, so the description must carry the load, and it does: it defines status as a terminal-status filter, days as 1..365 default 30, search as a campaign/adgroup/ad/id substring, and limit as 1..50 default 20. Only connection_context is left unexplained (a patterned context token, likely injected), which keeps this at 4 rather than 5.

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?

Names a specific verb and resource: 'List recent TikTok create task history for the current user.' The 'create task history' scope cleanly separates it from tasks_get_status or tasks_cancel, though it never explicitly contrasts with near-neighbors like tasks_list, tasks_latest, or tasks_get_create_detail.

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?

Gives a concrete trigger scenario ('Use this before comparing two launches such as ...') and rules out one misreading ('it does NOT call TikTok live APIs'). It stops short of naming an alternative tool or stating when NOT to call it, so an agent still has to infer the boundary against tasks_list / tasks_get_create_detail.

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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