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vnnivas

Reddit MCP Server

by vnnivas

Monitor Multiple Subreddits

reddit_monitor_subreddits
Read-only

Scan multiple subreddits for posts containing specific keywords. Returns keyword-matched discussions grouped by subreddit with scores, comment counts, and links.

Instructions

Scan multiple subreddits for posts matching specific keywords. Returns only posts whose title or body contain at least one keyword.

This is the primary tool for weekly Reddit intelligence digests — it scans target communities and filters for relevant discussions.

Args:

  • subreddits (string[]): List of subreddits to scan (e.g., ["nursing", "instructionaldesign", "humanresources"])

  • keywords (string[]): Keywords to match in post titles/body (e.g., ["compliance", "training", "onboarding", "policy", "video"])

  • time (string): Time window — "hour", "day", "week", "month" (default: "week")

  • limit_per_sub (number): Posts to fetch per subreddit, 5-100 (default: 50)

  • response_format (string): "markdown" or "json" (default: "markdown")

Returns: Filtered, keyword-matched posts grouped by subreddit with scores, comment counts, and links.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
timeNoTime window to scan: hour, day, week, monthweek
keywordsYesKeywords to filter for in post titles and body text (e.g., ["compliance", "training", "onboarding"])
subredditsYesList of subreddit names to scan (without r/ prefix, e.g., ["nursing", "instructionaldesign"])
limit_per_subNoPosts to scan per subreddit (default: 50)
response_formatNoOutput format: markdown or jsonmarkdown
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description only needs to add behavioral context. It does so by specifying that only posts matching at least one keyword are returned, and that results are grouped by subreddit with scores, comment counts, and links. No mention of rate limits or edge cases, but it gives solid insight beyond the annotations.

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

Conciseness5/5

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

The description is front-loaded with a one-sentence summary, followed by a contextual use case and a structured Args breakdown. Every sentence adds value, and the Returns section clearly describes the output. It is appropriately sized for a tool with five parameters.

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?

Since there is no output schema, the description must explain the return value, which it does with a clear summary of grouped, keyword-matched posts with scores, comment counts, and links. The main gaps are the time enum inconsistency and a lack of detail on the exact post fields returned, but overall it covers the essentials.

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 baseline is 3. The description repeats parameter examples and defaults, which is helpful, but it introduces a discrepancy: it lists the time window as 'hour, day, week, month' while the schema enum also includes 'year' and 'all'. This could mislead an agent into thinking those values are invalid.

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?

The description clearly states the tool scans multiple subreddits for posts matching keywords and returns filtered results. It distinguishes itself from sibling tools (get_posts, search_posts, get_comments) by focusing on multi-subreddit monitoring with keyword filtering, and the 'primary tool for weekly Reddit intelligence digests' clarifies its niche.

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 description clearly identifies the primary use case ('weekly Reddit intelligence digests') and explains that it scans target communities and filters for relevant discussions. However, it does not explicitly mention when not to use it or compare with alternatives, so it falls short of a 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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