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netanelavr

Trading MCP Server

by netanelavr

analyze_reddit_sentiment

Analyze retail investor sentiment from Reddit stock discussions across multiple subreddits. Get AI-powered sentiment analysis with confidence scores and key themes to gauge community opinion.

Instructions

Comprehensive Reddit sentiment analysis tool that searches for stock discussions across multiple investing subreddits and uses AI to analyze retail investor sentiment. Combines Reddit post search, optional comment extraction, and advanced sentiment classification to gauge community opinion and engagement. Use this when assessing retail investor sentiment, detecting sentiment shifts, or validating investment decisions against community consensus. Returns posts, sentiment analysis with confidence scores, key themes, and community engagement metrics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesStock ticker symbol
subredditsNoSubreddits to search for discussions
time_filterNoTime period to search withinweek
limitNoMaximum number of posts to retrieve
sortNoSort order for resultshot
max_posts_for_sentimentNoMaximum number of posts to use for sentiment analysis
include_commentsNoWhether to include comments from a specific post
post_id_for_commentsNoSpecific post ID to retrieve comments from (optional)
comment_limitNoMaximum number of comments to retrieve if include_comments is true
Behavior4/5

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

With no annotations, the description bears full responsibility. It discloses the tool searches multiple subreddits, optionally extracts comments, and performs AI sentiment classification with confidence scores, key themes, and engagement metrics. It doesn't mention rate limits or auth needs, but these are less critical for a read-only analysis tool.

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?

The description is three sentences long, front-loading the core purpose and use case. It is efficient but could be trimmed slightly for maximal conciseness. Each sentence adds value, earning a score of 4.

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?

Given 9 parameters (1 required), no output schema, and no annotations, the description covers the workflow: search, optional comment extraction, sentiment analysis, and returns (posts, sentiment with confidence, themes, engagement). It provides sufficient context for an agent to understand tool capabilities and output.

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%, baseline is 3. The description adds high-level context (e.g., 'combines Reddit post search, optional comment extraction, and advanced sentiment classification') but does not provide parameter-specific details beyond what the schema already documents. This meets the baseline.

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 identifies the tool as a 'comprehensive Reddit sentiment analysis tool' that searches stock discussions across multiple investing subreddits and uses AI to analyze sentiment. It differentiates from sibling tools (e.g., fundamental analysis, insider activity) by focusing specifically on social sentiment.

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 explicitly states when to use the tool: 'Use this when assessing retail investor sentiment, detecting sentiment shifts, or validating investment decisions against community consensus.' It lacks explicit when-not-to-use guidance, but usage context is clear given siblings cover different domains.

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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