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WhyFaust

Faust Threads MCP

by WhyFaust

threads_account_insights

Retrieve documented Threads account insights for a specified time window and metrics, providing clear analytics data for performance review.

Instructions

Fetch documented user insights with explicit coverage and window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinceNo
untilNo
metricsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The phrase 'with explicit coverage and window' hints that the caller must specify a metrics coverage and a time range, but the description does not state what happens when coverage is incomplete, how errors surface, whether auth is required, or what data availability constraints exist. Some signal is present, but far less than a no-annotation tool requires.

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

Conciseness3/5

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

The description is a single efficient sentence with the main verb front-loaded and no obvious filler. However, it borders on under-specification — 'documented' and 'user' add little, and the sentence is so terse that it sacrifices explanatory value rather than achieving disciplined brevity.

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?

For a tool with 3 undocumented parameters, no annotations, no output schema, and 5 siblings creating ambiguity, a 10-word description is grossly insufficient. Missing entirely are the expected time format, valid metric values, response shape, and any differentiation from sibling insight tools. The agent cannot correctly invoke this tool based on the provided definition 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?

Schema description coverage is 0%, so the parameters 'since', 'until', and 'metrics' carry only type information (integer, integer, array of strings). The description adds a minimal hint that since/until form a 'window' and metrics form 'coverage', which is helpful but still leaves format, units, and valid metric names entirely unspecified. The description does not meaningfully compensate for the zero-coverage schema.

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 identifies a specific operation ('Fetch') on a resource ('documented user insights'), which suggests account-level analytics and roughly separates it from publishing and latest-posts siblings. However, the word 'documented' is confusing and never explained, and the description does not clarify how this differs from threads_post_insights or threads_follower_demographics. The resource framing is decent, but the ambiguity about what 'documented' means prevents a higher score.

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?

No guidance is given about when to choose this tool versus any of its five siblings. There are no usage conditions, no exclusions, and no mention of alternatives like threads_post_insights for post-level data or threads_follower_demographics for demographic breakdowns. An agent comparing insight tools would have to guess which one fits the task.

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