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 skills add pedrohcgs/claude-code-my-workflow --skill lit-reviewgit 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/lit-review)<a href="https://agentmods.dev/skills/pedrohcgs/claude-code-my-workflow/lit-review"><img src="https://agentmods.dev/badge/skills/pedrohcgs/claude-code-my-workflow/lit-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/pedrohcgs/claude-code-my-workflow/lit-review"><img src="https://agentmods.dev/badge/skills/pedrohcgs/claude-code-my-workflow/lit-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00088 | $0.01148 |
| Opus 5 | $0.00044 | $0.00574 |
| Sonnet 5 | $0.00018 | $0.00230 |
| Haiku 4.5 | $0.00009 | $0.00115 |
Grade A, and why
lit-review 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 10d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- lit-review — 98% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Literature Review
Conduct a structured literature search and synthesis on the given topic.
Input: $ARGUMENTS — a topic, paper title, research question, or phenomenon to investigate.
Steps
-
Parse the topic from
$ARGUMENTS. If a specific paper is named, use it as the anchor. -
Search for related work using available tools:
- Check
master_supporting_docs/supporting_papers/for uploaded papers - Use
WebSearchto find recent publications (if available) - Use
WebFetchto access working paper repositories (if available) - Read any existing
.bibfile for papers already in the project
- Check
-
Organize findings into these categories:
- Theoretical contributions — models, frameworks, mechanisms
- Empirical findings — key results, effect sizes, data sources
- Methodological innovations — new estimators, identification strategies, inference methods
- Open debates — unresolved disagreements in the literature
-
Identify gaps and opportunities:
- What questions remain unanswered?
- What data or methods could address them?
- Where do findings conflict?
-
Extract citations in BibTeX format for all papers discussed.
-
Save the report to
quality_reports/lit_review_[sanitized_topic].md
Output Format
# Literature Review: [Topic]
**Date:** [YYYY-MM-DD]
**Query:** [Original query from user]
## Summary
[2-3 paragraph overview of the state of the literature]
## Key Papers
### [Author (Year)] — [Short Title]
- **Main contribution:** [1-2 sentences]
- **Method:** [Identification strategy / data]
- **Key finding:** [Result with effect size if available]
- **Relevance:** [Why it matters for our research]
[Repeat for 5-15 papers, ordered by relevance]
## Thematic Organization
### Theoretical Contributions
[Grouped discussion]
### Empirical Findings
[Grouped discussion with comparison across studies]
### Methodological Innovations
[Methods relevant to the topic]
## Gaps and Opportunities
1. [Gap 1 — what's missing and why it matters]
2. [Gap 2]
3. [Gap 3]
## Suggested Next Steps
- [Concrete actions: papers to read, data to obtain, methods to consider]
## BibTeX Entries
```bibtex
@article{...}
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.
- 10d ago First seen · 123 lines · 88 tokens per session scan A 7cd12baa0358
lit-review is a skill published in the GitHub repository pedrohcgs/claude-code-my-workflow (1,569 stars, last pushed 16d ago), licensed MIT. It adds 88 tokens to every session and 1,148 once invoked, about $0.0004 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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