claude-code-my-workflow is a forkable setup for using Claude Code to produce and review academic papers, slides, data analyses, and replication packages. Researchers use its agents, skills, rules, hooks, and quality checks to coordinate these tasks and verify their results. The catalogue entries define the reusable workflow components for Claude Code.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/pedrohcgs/claude-code-my-workflow/replication-packagenpx skills add pedrohcgs/claude-code-my-workflow --skill replication-packagegit clone --depth 1 https://github.com/pedrohcgs/claude-code-my-workflowWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/pedrohcgs/claude-code-my-workflow/replication-package)<a href="https://agentmods.dev/skills/pedrohcgs/claude-code-my-workflow/replication-package"><img src="https://agentmods.dev/badge/skills/pedrohcgs/claude-code-my-workflow/replication-package.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00145 | $0.02628 |
| Opus 5 | $0.00072 | $0.01314 |
| Sonnet 5 | $0.00029 | $0.00526 |
| Haiku 4.5 | $0.00015 | $0.00263 |
Grade A, and why
replication-package scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Replication Package
Produce the deposit an economist hands a journal at acceptance: a directory tree (data/, code/, output/, README) plus a DCAS compliance checklist, built to the AEA Data and Code Availability Standard, openICPSR deposit expectations, and the Social Science Reproduction Platform reproduction protocol. This skill moves the repo from auditing reproducibility to producing the deposit — /audit-reproducibility proves the numbers; this skill packages everything a third party needs to regenerate them from scratch.
Core principle: the package is reproducible by a stranger with the data and the README — no tacit knowledge, no "ask the author" steps. Every table and figure maps to the exact script and line that produces it.
When to use
- At acceptance. The journal's data editor (AEA, REStud, JPE, EJ, ...) requests a DCAS-compliant deposit before the paper is typeset.
- Before an openICPSR / Zenodo / Dataverse upload. Build the tree and README once, locally, before the web upload.
- Pre-submission dry run. Catch the "I never wrote down where Table 3 comes from" gap while it is cheap to fix.
- Confidential-data papers. Produce the access-restricted-data note and a runnable-on-restricted-data package even when the data itself cannot be deposited.
Inputs
$0— path to the manuscript (.tex,.qmd,.md,.pdf). Required (the source of the Table/Figure inventory).$1— outputs directory. Defaults toscripts/R/_outputs/. Recognised alternatives:scripts/stata/_outputs/,scripts/python/_outputs/,_targets/objects/.
Workflow
Phase 0: Pre-flight — detect language(s) and outputs
- Detect the analysis language(s) by scanning for
scripts/R/*.R(+renv.lock/DESCRIPTION),scripts/stata/*.do,scripts/python/*.py(+requirements.txt/environment.yml/pyproject.toml). A project may be polyglot — record all detected languages. - Locate the outputs directory (
$1) and the one-command entry point (00_run_all.R,99_run_all.do,run.py,Makefile). If none exists, flag it — DCAS requires a single master script. - If
quality_reports/passports/<paper-slug>.yamlexists, load it; itsclaims:entries are the authoritative Table/Figure →source_file:source_linemap for Phase 1.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 136 lines · 145 tokens per session scan A fbea5d1e9b79
replication-package is a skill published in the GitHub repository pedrohcgs/claude-code-my-workflow (1,556 stars, last pushed 11d ago), licensed MIT. It adds 145 tokens to every session and 2,628 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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