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tiktok get events

tiktok_get_events
Read-onlyIdempotent

Discover pixel or app events and accessible tracking diagnostics for an advertiser, using endpoint checks and reporting fallbacks.

Instructions

Discover pixel/app events or accessible tracking diagnostics for an advertiser. Uses best-effort endpoint checks plus reporting dimensions as fallback.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bcIdNoOptional Business Center ID. Defaults to TIKTOK_BC_ID/TIKTOK_BUSINESS_CENTER_ID for BC pixel discovery.
appIdNoOptional TikTok app ID for app event lookup when the endpoint is available.
limitNoMaximum number of returned items or rows. The declared bounds and default apply; use pagination for additional results.
endDateNoEnd date YYYY-MM-DD for tracking diagnostics. Defaults to today.
pixelIdNoOptional pixel ID for pixel event lookup.
startDateNoStart date YYYY-MM-DD for tracking diagnostics. Defaults to 7 days ago.
advertiserIdYesTikTok advertiser ID

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesOriginal tool result: parsed JSON when the text is JSON, otherwise the text or multiple MCP content blocks. Provider fields depend on the selected query.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.1

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context with 'best-effort endpoint checks plus reporting dimensions as fallback', but it does not disclose rate limits, error conditions, or what happens when endpoints are unavailable.

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?

Two sentences with no filler: the core purpose is front-loaded, and the fallback mechanism is stated compactly. Every phrase earns its place.

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 an output schema, full parameter descriptions, and annotations covering read-only/idempotent behavior, the description is largely complete. The only noticeable gap is that 'best-effort endpoint checks plus reporting dimensions as fallback' is not expanded, but structured data makes up for most of that ambiguity.

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 100%, and each parameter (advertiserId, bcId, appId, pixelId, date range, limit) is already fully documented. The description adds no parameter-specific meaning beyond what the schema already provides, so the baseline score of 3 applies.

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?

The description names a specific resource ('pixel/app events or accessible tracking diagnostics') and scopes it to an advertiser, which distinguishes it from list-style siblings like tiktok_get_pixels. The verb 'Discover' is slightly vague, but the object is concrete enough for an agent to identify the tool's job.

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?

The description implies the use case: finding pixel/app events and tracking diagnostics for an advertiser. It does not explicitly state when to prefer this over alternatives or name any sibling alternative, so selection guidance relies mainly on inference from the purpose.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.