# jordan-gibbs/hyperresearch

Agent-driven research knowledge base. Agents collect, search, and synthesize web research into a persistent, searchable wiki.

Repository: https://github.com/jordan-gibbs/hyperresearch
Canonical: https://ross.abutalabs.com/products/hyperresearch
Language: Python
License: MIT
License Family: permissive
Topics: agents, agentskills, claude-code, deep-research, deep-research-agent
Last push: 2026-08-04T19:37:19+00:00

## Health v2 (maintenance only)
Score: 78/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 96, release rhythm 95, longevity 10
- inputs: {"age_days": 146, "days_push": 29, "days_rel": 39, "gap_med": 1.5, "n_releases_24m": 11}
- flags: young
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1795, forks 206 (observed 2026-08-28T04:05:37.217872+00:00)

## What it is
Hyperresearch is a Python CLI harness that turns Claude Code into a deep research agent running a 16-step adversarially-audited pipeline. It produces cited research reports with full provenance and stores every source in a persistent, searchable markdown-plus-SQLite knowledge vault.

## Use cases
- run deep research on a topic from a single prompt
- generate cited research reports with verified sources
- build a persistent searchable research knowledge base
- find open-access copies of paywalled papers
- audit citations for hallucinated quotes and syndicated sources
- resume interrupted research runs
- reuse collected sources across research sessions

## When to choose
- you need long-form, citation-audited research reports rather than quick LLM answers
- you use Claude Code and want a disciplined deep-research workflow
- you want research sources accumulated in a reusable knowledge vault
- provenance and source independence matter for your reports

## When to avoid
- you need a hosted research product with no local setup
- you don't use Claude Code or LLM agent workflows
- you need real-time data rather than deep multi-source synthesis
- you require independently benchmarked performance - third-party validation is pending

## Facets
- artifact type: cli-tool
- maturity: active
- function: agent-framework, rag, search-engine, llm-inference, cli, web-scraping, markdown
- domain: artificial-intelligence, developer-tools
- platform: python, cli, cross-platform
- tags: deep-research, claude-code, knowledge-base, zettelkasten, citation-verification, research-agent, wiki, ai-agents, retrieval-augmented-generation, command-line, natural-language-processing

## Member repositories
- jordan-gibbs/hyperresearch (main) score 78

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:37.217872+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:22:51.398920+00:00, confidence not recorded.
  - readme: https://github.com/jordan-gibbs/hyperresearch (fetched 2026-08-28T04:05:37.217872+00:00, sha 878eb66e7b63)
  - registry_pypi: https://pypi.org/pypi/hyperresearch/json (fetched 2026-08-29T11:01:38.212212+00:00, sha 7b56c50bac8f)
- Data as of 2026-08-30T08:39:29.467469+00:00.