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hyperresearch vs prime-agent

Deep-research harness for Claude Code: a 16-step, tier-adaptive pipeline with adversarial critics, cite-checking and 250+ sources per run, every source kept in a persistent markdown+SQLite vault. — versus — Self-improving coding/research agent around a Recursive Language Model: persistent IPython as the core tool, programmatic subagents, durable harness state it refines via evidence-backed /refine.

The curated verdict

Both are self-improving research agents that keep state across sessions; prime-agent centers an RLM + IPython, hyperresearch a fixed adversarial pipeline inside Claude Code.

hyperresearchprime-agent
Stars3.4k21k
Forks3362.3k
LanguagePythonTypeScript
LicenseMITMIT
Last activity7 days ago2 days ago
Topicsagents, rag, skillscoding, agents
Curated connections56

hyperresearch — the curator's take

The most serious open deep-research pipeline you can run inside Claude Code: width sweep, contradiction graph, parallel depth investigators, four adversarial critics and a tool-locked patcher that can only apply surgical edits. Scholarly search fans out to OpenAlex/Crossref/CORE/EDGAR/FRED and it fetches legal OA full-text for paywalled papers instead of citing abstracts. Use it for reports you would otherwise pay a research analyst for; the vault means the second run on a topic starts warm. Not for quick lookups - even the 5-step fast path is minutes and the full pipeline is 30 min to hours of Claude Code time, plus your Max quota. Locked to Claude Code (uses the Skill tool for step loading); last30days-skill is the fast social-signal alternative, openresearcher is the trained-model route.

prime-agent — the curator's take

The two abstractions are genuinely different: context as variables in a persistent REPL (not a transcript), and a harness that rewrites its own supplemental state with rollback — the closest thing to a shipping continual-learning agent. Daemon sessions and agent-to-agent messaging make it a long-horizon tool, not a chat CLI. When NOT: it's a full worldview — you adopt the RLM way or fight it; young codebase moving fast, and self-improvement means your harness drifts from everyone else's.