Claude Code My Workflow: A Forkable Academic Automation Template with Real Quality Gates
Project brief: A ready-to-fork Claude Code template for academics using LaTeX/Beamer + R. Multi-agent review, quality gates, adversarial QA, and replication protocols.
At a glance
- What is it?
- This template packages Claude Code for academic work: multi-agent review, ten automated gates, adversarial QA, and replication protocols. It is not a plugin but a governance layer, and its default bypass permissions are a trade-off you need to understand before forking.
- Who is it for?
- Adopt this template if you are an academic who uses LaTeX, Beamer, Quarto, or R and you want a structured, gate-enforced AI workflow that checks its own work. Do not adopt it if you need a minimal, prompt-only tool or if you cannot tolerate the default bypass permissions; you must first verify that .claude/settings.json is adjusted to your risk tolerance and that the pre-commit hooks are installed.
- Can I use it commercially?
- Yes. MIT is a permissive licence: you can use, modify and sell software built on it, as long as you keep its copyright and licence notices.
- Is it still maintained?
- Yes. The repository last received commits 22 days ago.
- What is it written in?
- Mainly HTML, according to GitHub's language statistics.
Answers come from the project's GitHub data, last synced on September 15, 2026, and from our analysis. They are not legal advice.
DEEP OPEN-SOURCE ANALYSIS
What This Template Actually Solves
The repository pedrohcgs/claude-code-my-workflow addresses a specific pain: academics who use Claude Code for research outputs often end up with unstructured prompts, inconsistent quality, and no way to verify that an AI-generated LaTeX slide deck or R analysis is correct. This template provides a ready-to-fork foundation that turns a vague goal into a managed process. Instead of crafting a perfect prompt, you state a goal, and Claude plans, runs specialized agents, fixes issues, verifies quality, and presents results. The intended user is a researcher or lecturer who produces slides, papers, data analyses, or replication packages, and who is comfortable with git and command-line tools. The README is explicit that the template is extracted from a production PhD course, so it carries real-world teaching and research baggage, not just toy examples.
The v2.0 Shift: Goal-First, Gate-Enforced Work
The README describes a major shift in version 2.0: you do not craft a perfect prompt, you state a goal and let the work loop toward it under gates. The mechanism is a combination of specialist agents that do the labor and enforcing gates that decide when the output is good enough. You, the human, adjudicate disagreements that the agents surface. This is a different model from a single-agent chat where you review every step. The template ships with a set of rules and skills that orchestrate this loop. The key phrase is "real gates, not reminders." The gates are not just prompts that tell Claude to check its work; they are executable scripts that run checks against the repository state.
Setup and First Run: Commands That Matter
The quick start is concrete. You fork the repository on GitHub, then clone it locally. The first command is ./scripts/validate-setup.sh, which reports exactly what is missing with install links. This is a practical entry point because it tells you whether you have XeLaTeX, Quarto, Python, and git. The README warns that the first-time install may take about 30 minutes, but the 5 to 10 minute estimate is for the basic setup.
The Ten Gates and the Quality Scorer
The gate suite is the heart of the template. The README lists ten gates, but it does not detail every check in the truncated version. What is clear is that the gates cover both content and process. Surface-sync likely checks that files referenced in the documentation exist. Skill integrity verifies that the Agent Skills are well-formed. Model currency checks that the model references are up to date against a single source of truth. Link and anchor resolution catches broken links in the documentation. Agent Skills spec conformance ensures the skills follow the expected format. Staleness detects when the source files diverge from published outputs. Repo hygiene checks for common git issues. Derived counts re-count enumerable claims from disk, which is a clever way to catch outdated statistics. Ledger coverage is the most rigorous: it cross-checks the qualification ledger with the actual checks and hooks. Finally, the seeded hook battery re-fires every active guard hook against the failure it targets, alongside clean controls, on every run.
Adversarial QA and Replication Protocols
The template includes adversarial QA and replication protocols, though the README section is truncated. Based on the description, adversarial QA likely involves agents that try to break the output, such as testing edge cases in a data analysis or finding logical flaws in a paper. Replication protocols suggest that the template helps produce replication packages, which are common in economics and other social sciences. This is a differentiator from generic Claude Code setups, which rarely include such structured quality assurance.
Limitations and When It Is the Wrong Tool
The most obvious limitation is the default bypass permissions. The template ships with defaultMode: bypassPermissions and broad wildcard allows for Bash, Edit, and Write. This means that Claude Code can run arbitrary commands without prompting, which is a security risk if you fork the template and run it on a repository with sensitive data or untrusted content. The README acknowledges this and offers a way to tighten it, but the default is intentionally permissive. If you are not a power user, you might forget to change it.
Alternatives and How They Differ
A direct alternative is using Claude Code without any template, relying on Anthropic's built-in /init command to generate a CLAUDE.md from your codebase. The difference is that the template provides a pre-built academic workflow with gates and skills, while /init only creates a basic instruction file. The README explicitly mentions /init as a fallback for non-academic projects, so the template is not the only path.
Maintenance, Upgrades, and License
The project is actively maintained, with the last push on August 24, 2026, and three recent releases: v2.5.1 with an "enforcement" tag, v2.5.0 with "verification and currency," and v1.9.0 with a guide refresh. The CHANGELOG.md is the place to track changes, and the README says the project is extended by a community. The maintenance cost for you is that you need to keep your fork in sync with upstream changes, which can be done via git pull or by cherry-picking commits. The template's own gates include a staleness check that can help you detect when your fork diverges from the upstream source.
Editorial conclusion
Adopt this template if you are an academic who uses LaTeX, Beamer, Quarto, or R and you want a structured, gate-enforced AI workflow that checks its own work. Do not adopt it if you need a minimal, prompt-only tool or if you cannot tolerate the default bypass permissions; you must first verify that .claude/settings.json is adjusted to your risk tolerance and that the pre-commit hooks are installed. Also check the CHANGELOG for the latest v2.5.x changes and run ./scripts/validate-setup.sh before relying on any workflow. The project is actively maintained and MIT-licensed, but the real test is whether the ten gates and the adversarial QA fit your specific research artifacts.
Community notes