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datasets_reddit_trending_facets

Read-only

Return up to 50 facet buckets with counts for one Reddit trending field using the filters from datasets_reddit_trending_search. facet accepts subreddit, domain, or snapshot_date; page and page_size do not change counts; sort is validated but does not change bucket order. A snapshot_date facet without date spans all history. Other facets use the same search date scope: latest snapshot by default, full history for app_id or sort=date_desc, and only the requested day when date is supplied. Use datasets_reddit_trending_search to find trending posts.

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

NameRequiredDescriptionDefault
qNoOptional full-text query over the post title, max 256 characters.
dateNoOptional snapshot date filter, yyyy-MM-dd. Defaults to the latest available snapshot (today's trending).
pageNoResult page number, 1-based, default 1; page times page_size must not exceed 10000.
sortNoOptional sort order. Allowed values: rank (trending order), date_desc (a subreddit's history over time). Defaults to rank.
facetYesrequired,Required facet. Allowed values: subreddit, domain, snapshot_date.
page_sizeNoPage size, default 20, max 100; page times page_size must not exceed 10000.
subredditNoOptional exact subreddit-name filter (case-sensitive as tracked, e.g. webscraping).

Output Schema

NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

Annotations only declare readOnlyHint and openWorldHint; the description adds genuinely non-obvious behavior: page/page_size do not affect counts, sort is validated but does not reorder buckets, and the snapshot_date facet behaves differently from the others. The date-scope rules (latest snapshot by default, full history, or single day) are exactly the kind of subtle semantics an agent cannot infer elsewhere.

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?

Front-loaded with the purpose, then the facet values, then the scoping caveats, then the sibling routing. Every sentence carries information, though the middle date-scope sentence is a dense run-on that could be split for readability.

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?

Output schema exists, so return values needn't be explained, and annotations cover the safety profile; the description fills the remaining gap with facet and date-scope rules. The only hole is the dangling `app_id` reference, which does not map to any parameter this tool accepts.

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?

With 100% schema coverage the baseline is 3, but the description goes further by explaining the effect of page/page_size and sort on the output, and by spelling out facet-specific date semantics. It loses a point for referencing `app_id`, a parameter that does not exist in this tool's schema (additionalProperties is false), which could mislead an agent trying to pass it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: returns up to 50 facet buckets with counts for one Reddit trending field, and names the three allowed facet values. It also explicitly contrasts itself with the sibling `datasets_reddit_trending_search`, so an agent can distinguish the aggregation tool from the post-listing tool without opening either schema.

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?

The final sentence routes the agent explicitly ("Use datasets_reddit_trending_search to find trending posts"), making the aggregation-vs-listing split clear. The opening clause also ties it to the filters from that search tool. It stops short of stating when-not-to-use beyond that routing hint, so it lands at 4 rather than 5.

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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