Research Toolkit
Description
Reusable commands for structured AI-assisted research workflows. Plan-Construct-Verify (PCV), Council of Agents (CoA), Parallel Agent Consensus Engine (PACE), and workflow automation. Built and validated with real research sessions using Claude Code during research pursuing a PhD in Operations Research.
Installation
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open the source below and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
README
Research Amp Toolkit
*Every empirical value cites a file on disk. Every claim survives `grep`. Dissertation-grade, not vibe-grade.*
**⚠️ v0.1 — experimental, no support commitment.** This is an early research release under active development. Breaking changes expected between versions. Issues and pull requests are welcome; responses are best-effort, not guaranteed. If you're looking for a stable production tool, this isn't it yet.
15 Claude Code commands that amplify your research. The tools don't think — they verify, structure, and document. You bring the signal. Validated across hundreds of production sessions.
**Authors:** Jake Benhart & Dr. Michael G. Kay (NC State University — Operations Research)
**Links:** [Landing page](https://jbenhart44.github.io/Research-Toolkit/) · [Download v0.1](https://github.com/jbenhart44/Research-Toolkit/releases) · [Report an issue](https://github.com/jbenhart44/Research-Toolkit/issues) · [Discussions](https://github.com/jbenhart44/Research-Toolkit/discussions) · [Contribute](CONTRIBUTING.md)
Design rationale: [DESIGN.md](DESIGN.md). Who this is for and not for: [POSITIONING.md](POSITIONING.md). Error classes the toolkit is built to prevent: [references/preventable_errors.md](references/preventable_errors.md). Consolidated rule index: [references/iron_rules.md](references/iron_rules.md).
Spec-Driven Development
This toolkit is a working implementation of **Spec-Driven Development (SDD)** — the practice of writing the plan, constructing against it, and verifying the result as three separate, auditable steps rather than one conflated "just ask the model" loop. The commands here (`/pcv`, `/pace`, `/audit`, `/readable`, `/coa`) predate the SDD label; they grew out of PhD-research needs where a wrong citation or a hallucinated number is a career cost, not a minor bug. The SDD label is retroactive — the pattern became visible when the broader AI-engineering conversation converged on the same decomposition (peer implemen
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