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michael jackson bad

Project description

BAD — michael jackson bad

Bad Research

michael jackson bad

A keyless deep-research agent that runs as a Claude Code skill — a fork-and-enhance of hyperresearch. It searches wide, filters garbage, grounds every claim to a source, and needs zero API keys: the Claude Code host model supplies all inference, exactly like hyperresearch. Optional local CLIs and a [local] neural extra are enhancements, never requirements.

Install

Bad Research is a small CLI that registers itself as a Claude Code skill. No API keys. Requires Python 3.11–3.13.

# Install the CLI (pipx or uv — either works)
pipx install bad-research
uv tool install bad-research

# Register the /bad-research skill into ~/.claude
bad install

# Verify
bad doctor

bad install writes the entry skill to ~/.claude/skills/bad-research/; the per-step skills install lazily on first use. For a project-local install instead of global, run bad install --project inside the project. bad doctor shows what's wired (host model, keyless search/browse, the optional external CLIs it can drive, the [local] neural stack).

Use it in Claude Code

After bad install, open Claude Code in any project and either:

  • Invoke it directly — type the slash command with your question:
    /bad-research Is open-source AI more dangerous than closed-source for national security?
    
  • Let Claude trigger it — just ask a research-shaped question ("write me a cited report comparing vector databases", "literature review on GLP-1 drugs") and Claude loads the skill automatically.

It scales to the question: a simple lookup gets a fast cited answer in minutes; a broad or contested one runs the full adversarially-reviewed pipeline (~1.5–2.5 h). The final report and every fetched source land in a vault under ./research/ that compounds across sessions.

Want the latest unreleased build? Install from source: pipx install git+https://github.com/LeventySeven/badresearch.git

What it does

A tier-adaptive pipeline turns a question into an audited, fully-cited report, and every fetched source lands in a persistent, searchable vault that compounds across sessions. Keyless by design:

  • Search — the host WebSearch tool + DuckDuckGo + 7 scholarly APIs, fused and reranked by the host model.
  • Content — a native fetch-and-clean pipeline (readability → markdown → optional LLM clean), SSRF-guarded.
  • Browse — an agentic observe → act → extract loop driven by a local, keyless headless browser.
  • Retrieve — SQLite FTS5/BM25 by default (no model required), with an optional local neural lane.
  • Ground — every report sentence is checked against its source; uncited claims are blocked.

How it works & where the patterns came from

Bad Research takes hyperresearch as its base and enhances each stage with patterns drawn from the best deep-research systems — Perplexity, Gemini, Firecrawl, Stagehand, AgentQL, and others — reimplemented to run keyless on the host model. The full write-up, stage by stage with provenance, is in docs/HOW_IT_WORKS.md.

MIT licensed.

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