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datasets_reddit_trending_facets

Discover Reddit trending facet values by subreddit, domain, or snapshot date, returning up to 50 buckets ordered by count using the same filters as trending search.

Instructions

Discover values in the Reddit trending dataset. Returns up to 50 Reddit trending-facet buckets ordered by count, using the same filters as datasets_reddit_trending_search. Page and page_size do not change the aggregation. A snapshot_date facet without date spans all history; other facets use the search date scope, including the latest-snapshot default and full history for date_desc sort.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "facet": "<facet>"
    },
    "name": "datasets_reddit_trending_facets"
  }
}

Input Schema

Name	Required	Description
`q`	No	Full-text post-title query
`date`	No	Snapshot date, yyyy-MM-dd
`page`	No	Result page, 1-based
`sort`	No	Validated search sort; bucket order stays count-desc, and time-series date_desc keeps its search history scope
`facet`	Yes	Facet field
`page_size`	No	Page size, default 20 and max 100
`subreddit`	No	Exact subreddit name

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.17.20Nov 12, 2026

TDQS

A4/5.0

Behavior4/5

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

With no annotations, the description carries the burden and does meaningful work: it discloses the 50-bucket cap, count-descending ordering, and the non-obvious fact that page and page_size do not change the aggregation. It also discloses date-scope behavior that varies by facet. It stops short of describing permissions, error behavior, or exactly what fields each bucket contains.

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?

Three sentences, front-loaded with purpose and return shape, then the pagination caveat, then the date-scope nuance. No filler, though the density of the final sentence makes it slower to parse than ideal.

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 7-parameter aggregation tool with no output schema, the description covers the essentials an agent needs: return cardinality, ordering, pagination semantics, and facet-specific date scope. What is missing is a description of bucket shape (value plus count) and any statement of what happens when filters match nothing.

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 100%, so the baseline is 3, but the description adds real meaning beyond the schema: it clarifies that page/page_size are effectively display-only against a fixed aggregation, and that sort interacts with facet scope for date_desc. The facet enum values themselves are only explained via the date-scope sentence, which is the one partial gap.

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 the resource (Reddit trending facet buckets) and the operation (discover/aggregate values), and states the return shape: up to 50 buckets ordered by count. It explicitly ties itself to the sibling search tool by noting it uses the same filters, which helps an agent separate aggregation from search. The opening verb 'Discover values' is slightly abstract, keeping it out of the top band.

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?

It gives concrete usage context: filters mirror `datasets_reddit_trending_search`, and it spells out the date-scope rule per facet (snapshot_date without a date spans all history; other facets inherit the search date scope, including the latest-snapshot default and full history under date_desc sort). It does not state an explicit 'use this instead of search when...' rule, so the when-to-use is inferable rather than stated outright.

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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