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tokportal

tokportal-mcp

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by tokportal

tokportal_get_analytics_series

Read-onlyIdempotent

Retrieve time-series analytics data for a TikTok account by specifying date range, metric, granularity, and mode. Use it to track views, likes, comments, shares, or followers over time for performance analysis.

Instructions

Get analytics time series.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoquery parameter to
fromNoquery parameter from
modeNoquery parameter modecumulative
metricNoquery parameter metricviews
accountNoRepeatable account filter.
granularityNoquery parameter granularityday
Behavior2/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, covering basic safety. The description adds no behavioral context beyond that—no mention of scoping, pagination, or response characteristics. Since annotations already carry the safety profile, the description's lack of additional transparency is a missed opportunity.

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

Conciseness2/5

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

The description is extremely brief (one phrase) but under-specified. It does not front-load key information or structure content effectively. Every sentence should earn its place, but this single sentence conveys minimal useful information, making it insufficient rather than concise.

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

Completeness1/5

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

Given 6 parameters, no required ones, no output schema, and a complex context (many analytics siblings), the description is severely incomplete. It does not explain what the time series contains (e.g., metrics, accounts, date ranges), how defaults interact, or what the return format looks like. The agent cannot infer adequate usage or interpret results from this description alone.

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?

Although schema description coverage is 100%, the parameter descriptions are minimal (e.g., 'query parameter to') and add no meaning beyond the parameter name and type. The tool description itself does not explain parameter semantics. For example, the difference between 'cumulative', 'gained', and 'snapshot' mode is not clarified. With only tautological schema descriptions, the tool description fails to add value.

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 'Get analytics time series' identifies a specific resource (time series) and a verb (get), which is clear at a high level. However, it does not differentiate from many analytics siblings like tokportal_get_analytics_dashboard, tokportal_get_account_analytics, or tokportal_get_video_analytics. The purpose is moderately clear but lacks specificity about what aspect of analytics is captured.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus the many analytics siblings (e.g., when to use this instead of tokportal_get_analytics_dashboard or tokportal_get_account_analytics). There is no mention of context, prerequisites, or exclusions. This leaves the agent without decision-making information.

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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