Reddit Subreddit Sentiment Tracker
Uses the Reddit OAuth2 API via PRAW to collect top posts and comments from subreddits on a rolling 24-hour window, then runs batch sentiment scoring via HuggingFace Inference API using twitter-roberta-base-sentiment. Aggregates scores into a daily time-series written to Google Sheets for Looker Studio visualization. Fires Slack alerts when sentiment drops more than 20 points week-over-week.
Uses the Reddit OAuth2 API via PRAW to collect top posts and comments from subreddits on a rolling 24-hour window, then runs batch sentiment scoring via HuggingFace Inference API using twitter-roberta-base-sentiment. Aggregates scores into a daily time-series written to Google Sheets for Looker Studio visualization. Fires Slack alerts when sentiment drops more than 20 points week-over-week.
npx skills add agentskillexchange/skills --skill reddit-subreddit-sentiment-tracker
Reddit Subreddit Sentiment Tracker is built around Slack messaging and workspace APIs. The underlying ecosystem is represented by slackapi/bolt-js (2,900+ GitHub stars). It gives an agent a more technical and reliable way to work with the tool than a thin one-line wrapper, using stable interfaces like conversations.history, chat.postMessage, users.info, block kit, files and preserving the operational context that matters for real tasks.
In practice, the skill gives an agent a stable interface to slack so it can inspect state, run the right operation, and produce a result that fits into a larger engineering or operations pipeline. The original use case is clear: Uses the Reddit OAuth2 API via PRAW to collect top posts and comments from subreddits on a rolling 24-hour window, then runs batch sentiment scoring via HuggingFace Inference API using twitter-roberta-base-sentiment. Aggregates scores into a daily time-series written to Google Sheets for Looker Studio visualization. Fires Slack alerts when sentiment drops more than 20 points week-over-week. The implementation typically relies on conversations.history, chat.postMessage, users.info, block kit, files, with configuration passed through environment variables, connection strings, service tokens, or workspace config depending on the upstream platform.
- Accesses conversations.history, chat.postMessage, users.info, block kit, files instead of scraping a UI, which makes runs easier to audit and retry.
- Supports structured inputs and outputs so another tool, agent, or CI step can consume the result.
- Can be wired into cron jobs, webhook handlers, MCP transports, or local CLI workflows depending on the skill format.
- Fits into broader integration points such as chat triage, digests, alerts, and collaborative automation.
Key integration points include chat triage, digests, alerts, and collaborative automation. In a real environment that usually means passing credentials through env vars or app config, respecting rate limits and permission scopes, and returning structured artifacts that can be attached to tickets, pull requests, dashboards, or follow-up automations.