autoresearch
Autonomous iteration loop: modify, verify, keep/discard against any metric
8 personas interrogate requirements until constraints saturate
> /plugin marketplace add uditgoenka/autoresearch > /plugin install autoresearch@autoresearch
How it fires
How this command gets triggered: by you, by Claude, or both.
/probeContext preview
What this command does when you run it.
8 personas interrogate requirements until constraints saturate
name: autoresearch:probe description: "8 personas interrogate requirements until constraints saturate" argument-hint: "[Topic: <text>] [Scope: <glob>] [--depth shallow|standard|deep] [--personas N] [--mode interactive|autonomous] [Iterations: N] [--evals]"
EXECUTE IMMEDIATELY.
Extract from $ARGUMENTS:
AskUserQuestion (single batch): Q1 (Topic): "What to probe?" — open text describing feature, requirement, or design Q2 (Scope): "Which files for context?" — suggested globs + entire codebase Q3 (Depth): "How deep?" — shallow (5 rounds), standard (15), deep (30), unlimited Q4 (Mode): "How to answer persona questions?" — interactive (you answer), autonomous (agent infers from code) If all provided → skip.
| # | Persona | Focus | |---|---|---| | 1 | Domain Expert | Business rules, domain constraints, terminology | | 2 | End User | Usability, expectations, error recovery | | 3 | Skeptic | Assumptions that might be wrong | | 4 | Edge-Case Hunter | Boundary conditions, rare scenarios | | 5 | Ops Engineer | Deployment, monitoring, scaling, failure modes | | 6 | Security Reviewer | Attack vectors, data protection, auth | | 7 | Contradiction Finder | Conflicts between requirements | | 8 | Scope Guardian | Feature creep, unnecessary complexity |
If --adversarial: rotate Skeptic + Contradiction Finder + Edge-Case Hunter to front.
Append to output: round number, personas active, questions asked, constraints extracted, net-new count
If --evals: check if current_round % interval == 0 → run checkpoint.
If bounded: current_round >= max_iterations → exit loop.
Create output directory: `autoresearch/probe-{YYMMDD}-{HHMM}/`
1. Write `constraints.md` — full constraint registry organized by category 2. Write `conflicts.md` — unresolved contradictions 3. Generate ready-to-run autoresearch config:
Print: total rounds, constraints found, saturation status, unresolved conflicts.
Print: total rounds, total constraints, net-new trend, saturation status, top 5 most impactful constraints.
If --evals present:
Write handoff.json: version "2.1.0", source "probe", timestamp, status (COMPLETE|SATURATED|USER_INTERRUPT|BOUNDED|ERROR), findings = constraints, config = derived autoresearch config. Invoke next target in --chain order. Propagate --evals flag.
Turn Claude Code, OpenCode, or OpenAI Codex into a relentless improvement engine. Based on Karpathy's autoresearch — constraint + mechanical metric + autonomous iteration = compounding gains.
Repo: uditgoenka/autoresearch
Autonomous iteration loop: modify, verify, keep/discard against any metric
Analyze iteration results: trends, plateaus, regressions, recommendations
Scout codebase and auto-generate docs — or a navigable wiki knowledge base — with validation-fix loop