last30days-research: Time-Boxed Research for Agents

Where this fits

A user asks your agent what people are saying about the new pricing tier on Reddit and Twitter this month. Without a time-boxed research skill, the agent either guesses from stale training data or runs a scattered web search. last30days-research gives agents a structured workflow to pull recent activity across Reddit, Twitter, YouTube, Hacker News, news, and general web search through SandBase, and cross-reference it into a usable brief.

Why agents benefit

• Queries at least 3-4 platforms per topic by default, so coverage is broad enough to catch platform-specific reactions.
• Weights recent signals more heavily, making conclusions reflect the last 30 days instead of an average of mixed dates.
• Notes platform bias explicitly: Reddit for technical, Twitter for real-time, YouTube for educational; the skill can adjust interpretation.
• Cross-references findings and produces a confidence score, reducing single-source hallucination.
• Reports when mentions spiked or changed tone, which is useful for launch reactions and sudden shifts.

Practical scenarios

Launch-reaction monitoring

An agent can answer how developers reacted to the latest SandBase release by pulling posts from Hacker News, Reddit, and YouTube and summarizing the dominant sentiment with a timeline of spikes.

Competitor activity scan

A sales enablement agent can research a competitor's latest feature release across news and Twitter, identifying customer pain points and positioning talking points for the last 30 days.

Current profile check

Before a call, an agent can build an updated profile of a person or company from recent news, YouTube interviews, and web results, flagging changes from older assumptions.

Add it to your agent workflow

Install via npx:

npx skills add sandbaseai/sandbase-skills --skill last30days-research

Then instruct the agent with a clear task:

Research the last 30 days of public reaction to the Llama 4 release.
Use last30days-research, query at least 4 platforms, and give me a timeline of sentiment changes.

Compare before adopting

Check whether the skill's code remains fresh: last commit, open issues, and response time from the maintainer. Compare it against alternatives like direct SandBase API calls, general web-search skills, or manual searching. Also verify it fits your stack: if you already use SandBase for tool calls, this skill lowers integration cost; if not, the added dependency is worth evaluating. Look for quality signals like platform bias notes and confidence scoring in the output.

Why it is worth tracking

The skill has 68 stars and a clear design philosophy: recency-weighted, cross-platform, and transparent about source bias. That is a good baseline for a time-boxed research agent. OpenAgentSkill tracks its evolution; for a live listing, visit last30days-research on OpenAgentSkill. If you are building agents that answer current events, competitor moves, or product feedback, keep this on your evaluation list and re-check after major updates.