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Get Threads User Insights

threads_get_user_insights
Read-only

Retrieve account-level Threads metrics: views, likes, replies, reposts, quotes, followers count, reach, and follower demographics broken down by age, country, city, or gender.

Instructions

Gets account-level metrics for the authenticated Threads user.

Args:

  • threads_user_id (string): Threads user ID

  • metrics (string[]): Options: Time-series: views, likes, replies, reposts, quotes, followers_count, reach Demographics: follower_demographics (breakdown by age, country, city, gender — requires 100+ followers)

  • since (string, optional): Start date YYYY-MM-DD (required for time-series metrics)

  • until (string, optional): End date YYYY-MM-DD

  • breakdown (string, optional): For follower_demographics: 'age', 'country', 'city', 'gender'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinceNo
untilNo
metricsNo
breakdownNoFor follower_demographics metric only
response_formatNoOutput format: 'markdown' for human-readable or 'json' for machine-readablemarkdown
threads_user_idYes
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds useful behavioral constraints: follower_demographics requires 100+ followers and since is required for time-series metrics. No contradictions found. It doesn't cover rate limits or auth, but those are not needed for a read-only operation.

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?

The description is organized as a bulleted list of arguments with clear labels. It is front-loaded with the main purpose and then details parameters efficiently. No wasted words, though it could be slightly tighter.

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?

Given the tool has 6 parameters and schema covers only breakdown and response_format, the description explains most parameters and their constraints. It omits response_format (but schema documents it) and default metrics (schema has default). Overall, it covers all critical usage details for correct invocation.

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 coverage is only 33% (only breakdown and response_format have descriptions), but the description compensates by explaining the metrics list, since/until format, breakdown options, and dependencies. It adds significant meaning beyond the schema, especially for metrics and date parameters.

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 clearly states it 'Gets account-level metrics for the authenticated Threads user.' This is a specific verb-resource pair that distinguishes it from per-post tools like threads_get_post_insights, though it does not explicitly name that sibling. The scope is evident from 'account-level.'

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 provides context (account-level vs. post-level, follower threshold for demographics, since required for time-series) but does not explicitly route users to alternative tools. It implies usage based on scope and requirements, but lacks direct comparisons to siblings like threads_get_post_insights.

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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