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JavaScript
Remote

reddit_comments

Fetch public comments from a Reddit post by ID, with optional sorting, depth, and engagement metrics for analysis or moderation.

Instructions

Get Reddit post comments. Returns a Reddit post with its public comments. The default 1-credit mode uses RSS. Set include_metrics=true to use the anonymous HTML post page as the sole content request and return the server-rendered comments with public net score and award count plus post engagement metrics for 3 credits. Large threads may expose only an initial comment subset in anonymous HTML. Reddit does not expose per-comment upvote ratios or exact upvote/downvote totals anonymously. A post that exists but has no comments yet returns a 200 response with an empty comments list; a post that does not exist returns 404, and a temporary block or upstream failure returns 503 (retryable) rather than 404. Native-source failures can use the internal Redlib fallback; source.type is redlib and public fields/credit weights are preserved.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesReddit post id or t3_ id
sortNoComment order: confidence, top, new, controversial, old, or qa. Applied to the anonymous HTML request when metrics are enabled.
depthNoMaximum flat comment depth returned in metrics mode.
limitNoMaximum comments returned, defaults to 25 and clamps to 100
include_metricsNoInclude public post and per-comment engagement metrics; costs 3 credits instead of 1

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / sort / enum
      Added value: +[
+  "confidence",
+  "top",
+  "new",
+  "controversial",
+  "old",
+  "qa"
+]
  2. Changed3 schema fields changed
    • changedInput schema / properties / depth / description
      Previous value: -"Accepted for compatibility. Public comment data is flat and may ignore depth."New value: +"Maximum flat comment depth returned in metrics mode."
    • addedInput schema / properties / include_metrics
      Added value: +{
+  "description": "Include public post and per-comment engagement metrics; costs 3 credits instead of 1",
+  "type": "boolean"
+}
    • changedInput schema / properties / sort / description
      Previous value: -"Accepted for compatibility: confidence, top, new, controversial, old, or qa. Public comment data is flat and may ignore sort."New value: +"Comment order: confidence, top, new, controversial, old, or qa. Applied to the anonymous HTML request when metrics are enabled."
  3. Changed1 schema field changedv1.5.0
    • removedInput schema / properties / with_scores
      Removed value: -{
-  "description": "When true, source comment scores and nested replies from old.reddit HTML rather than the default (slower)",
-  "type": "boolean"
-}
  4. Changed1 schema field changedv1.2.0
    • addedInput schema / properties / with_scores
      Added value: +{
+  "description": "When true, source comment scores and nested replies from old.reddit HTML rather than the default (slower)",
+  "type": "boolean"
+}
  5. First observedv1.0.0

TDQS

A4/5.0
Behavior5/5

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

With no annotations to lean on, the description carries the full behavioral burden and does so richly: it discloses credit costs per mode, the 200-with-empty-list / 404 / 503-response semantics, the fact that large threads expose only an initial comment subset, anonymous-data limits (no upvote ratios or exact totals), and a Redlib fallback that preserves source.type and credit weights.

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 purpose and mode selection, then the operational caveats. It is dense but every sentence carries distinct information (modes, cost, data limits, status codes, fallback), with little redundancy.

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

Completeness5/5

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

No output schema or annotations exist, so the description must cover return content, error/status behavior, data limitations, and fallback behavior — and it does all of these. An agent has everything needed to call it correctly and interpret responses.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents id, sort, depth, limit, and include_metrics, including the 3-credit cost and the sort-applies-in-metrics-mode note. The description largely restates this (include_metrics cost, sort in anonymous HTML mode) rather than adding new parameter meaning, so the baseline 3 is appropriate.

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 opens with a specific verb+resource ("Get Reddit post comments") and clarifies the return shape ("a Reddit post with its public comments"). It does not, however, distinguish itself from close siblings like reddit_post, reddit_subreddit_comments, or reddit_user_comments, leaving the agent to infer the boundary from the name alone.

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?

It clearly documents the two operating modes and the trigger for switching ("Set include_metrics=true ...") along with the credit tradeoff, which is genuine usage guidance. But it never states when to reach for this tool versus reddit_post or the subreddit/user comment siblings, so alternate-tool routing is left implicit.

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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