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Last30Days Skill
Last30Days Skill gathers recent discussion and activity around a topic for an AI assistant to turn into a linked research brief.
It combines a Python research engine with instructions for the host assistant. Sources can include Reddit, Hacker News, GitHub, X, video transcripts, and the web, depending on the services and credentials available. Use this as a first read, not a recommendation. Open the original project before trusting details like terms, limits, privacy, cost, setup, or safety.
What it is
A reusable recent-topic research workflow
Give an agent a topic and the skill gathers material from a recent date window, ranks retrieved evidence, and supplies source links for the resulting brief. Thirty days is the default window; the engine also accepts a different lookback.
Why it stands out
Discussion and activity alongside web coverage
The workflow brings together material such as Reddit comments, GitHub activity, and video transcripts. Engagement counts help order the material, while topic matching checks whether an item concerns the subject being researched. Those signals help with discovery; they do not establish that a claim is true.
Availability
An installable skill with optional source connections
The project documents installation for Claude Code, Codex, Cursor, Copilot, Gemini CLI, and other Agent Skills hosts. Reddit, Hacker News, Polymarket, and GitHub have paths without extra source credentials. Additional channels depend on API keys, other tools, or an authorized browser session.
Why it matters
What makes it useful
Before revising a tutorial or trying an AI tool, you may want to know what people have been encountering recently. A topic request can bring back discussions, project activity, and explanations to follow up. The project gives examples involving tool research, prompt techniques, and preparation for meetings. The useful starting point is a specific question: which problems are people reporting, what changed, or which approaches are they trying?
What to know
Where it fits
The skill runs inside a compatible assistant with permission to execute its scripts and reach the selected sources. Its engine retrieves and prepares evidence; the host assistant plans applicable searches and writes the ordinary research summary. Where the host provides web search, that search also supplies supporting material. Installing the skill does not give every source access automatically, and this is a setup task for an agent environment rather than a standalone browser search box.
Notable points
What stands out
Coverage has several possible outcomes. A source can complete a search with no matches, fail authentication, time out, or return only partial results. The skill tells the assistant to preserve those differences in the brief. If X is unavailable, an empty X section cannot tell you that nobody discussed the topic there. This makes the coverage information worth reading alongside the findings, especially when comparing two topics searched with different available channels.
Before using
What to review
Check the runtime and installation instructions for your chosen assistant. The project requires Python 3.12 or newer, and source diagnosis can show which connections are available.
Some additional sources use paid API services. Check the selected providers and their current terms before adding keys; an assistant subscription does not necessarily include those services.
Browser-backed access is optional and consent-based in the documented setup. You can skip it and continue with available sources. Review which session would be used before granting access.
The default research-save location is a Documents/Last30Days folder. Configuration can change that location or disable saves. Optional local-file search also needs an explicit choice of folders.
Open the underlying sources before relying on an important claim. A busy discussion or a highly ranked result shows attention, which may include disagreement, repetition, or error.
Reader fit
Who may find it relevant
Relevant to writers, researchers, and practical AI builders who already use an agent and want recent leads before doing deeper work. Someone comfortable installing a skill and choosing source connections has a clearer path to trying it. A reader who wants a finished, independently verified report may prefer to use the linked discussions and documents as starting material for their own research.
Editorial note
Why LifeHubber lists it
We list Last30Days because it brings recent community discussion into the same research task as project activity and web coverage. For someone updating an explanation, the questions and difficulties appearing in those discussions can suggest what the explanation needs to address. The linked brief gives them places to investigate before deciding what to change. Its value is in finding those leads across several channels, with source access and missing coverage still visible.
Source links
Source materials
Reader note
Before relying on this entry
LifeHubber lists entries to help readers inspect AI projects, not to endorse them or prove they are safe, suitable, accurate, maintained, or right for a specific use. We do not verify every entry in depth. Before relying on anything listed, review the original materials, terms, privacy practices, limits, and risks that matter for your situation.
What to explore next
Turn recent signals into checked evidence.
A cross-source sweep can show what people are discussing. Continue by understanding how AI search assembles an answer, then check important claims before using them.
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