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AdsAgent — TikTok Ads MCP

Delete an interest pack

interests_archive
Destructive

Archive an existing saved interest pack owned by the authenticated user. Mirrors Meta interests_archive — wire name preserved across products even though TikTok implements this as a hard delete (the TikTok schema does not yet expose a soft-archive status column). After this call the pack no longer appears in interests_list.

REQUIRED: interest_pack_id (str). EXAMPLE: interests_archive({"interest_pack_id": ""})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
interest_pack_idYes
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

A4.3/5.0
Behavior5/5

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

Annotations already declare destructiveHint=true and readOnlyHint=false, and the description adds genuinely non-obvious context: the 'archive' name masks an irreversible hard delete because no soft-archive status column exists yet. It also states ownership scoping ('owned by the authenticated user') and the observable post-condition. This is exactly the kind of disclosure an agent needs before invoking a destructive tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

Front-loaded with the action and the critical naming caveat before the mechanics. The REQUIRED/EXAMPLE block is efficient, though the example line restating the same call format is slightly redundant against the schema.

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 tool with no output schema, it covers the key concerns: ownership, irreversibility, and post-call state. The only gap is the undocumented optional connection_context parameter, which is a minor omission given the tool's single required input.

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 the parameter burden. It documents the required interest_pack_id as a str with a UUID-shaped example, which is useful, but says nothing about connection_context (the second, optional param) or any format constraints on it.

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 ('Archive an existing saved interest pack owned by the authenticated user') and immediately resolves the naming ambiguity by explaining that the wire name is preserved from Meta but TikTok implements it as a hard delete. It also positions the tool relative to siblings by noting the pack disappears from interests_list afterward.

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 clear context for when to call it (removing an existing, user-owned pack) plus a post-condition that lets an agent verify the outcome against interests_list. It does not explicitly name alternatives (e.g. why to archive vs. simply stop listing) or state exclusions, so it falls short of a full when/when-not treatment.

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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