last30days

Research any topic across Reddit, X, YouTube, TikTok, Instagram, Hacker News, Polymarket, GitHub, Perplexity, and more. AI agent scores by upvotes, likes, and real money. Also triggered by 'last30'.

This skill includes substantial runnable code and persistent storage but the registry metadata (no required env vars or binaries; no install) does not reflect that. Before installing or providing credentials: 1) Inspect and run the built-in diagnostic: python3 <skill_root>/scripts/last30days.py --diagnose to see which sources require keys and which binaries are missing. 2) Do NOT paste account tokens (AUTH_TOKEN/CT0 or others) unless you understand the risk — X tokens can grant access to your account data. Prefer read-only or scoped keys where possible. 3) If you want to try safely, run the scripts in an isolated environment (container or throwaway VM) and avoid writing secrets to ~/.config until satisfied. 4) Verify required binaries (node, yt-dlp) are acceptable to install on your system — node is required to run the vendored bird-search module. 5) Be cautious about enabling cron/automatic runs or running the setup/device-auth flows; those will persist configuration and may schedule recurring networked activity. 6) If you plan to use the skill, consider limiting credential scope, reviewing the vendored JS (bird-search.mjs), and confirming which backend (ScrapeCreators vs OpenAI/Perplexity/OpenRouter) the current variant actually uses (there are conflicting references).

Type: OpenClaw Skill Name: last30days-official Version: 3.0.0-open The skill is a comprehensive research and monitoring tool that aggregates data from multiple social media platforms (Reddit, X, YouTube, TikTok, Instagram) and web sources. It features a sophisticated orchestration pipeline including intelligent pre-research (auto-resolution of handles/subreddits), a SQLite-backed knowledge accumulator with full-text search, and a 'fun judge' LLM-scoring mechanism. While the skill utilizes high-privilege tools like Bash for dependency management (installing yt-dlp via Homebrew) and allows the agent to modify its own configuration file (~/.config/last30days/.env) for user-requested toggles like ELI5 mode, these behaviors are transparently documented and strictly aligned with the stated purpose. The code includes security best practices such as checking file permissions on secrets files (lib/env.py) and using structured subprocess calls rather than raw shell execution. No evidence of malicious intent, unauthorized data exfiltration, or obfuscation was found.