Codeg is a collaborative workspace that brings multiple AI coding agents and their sessions into one searchable application. Developers use it to coordinate agents, delegate work, and review unattended coding tasks across desktop, server, Docker, and mobile clients. The catalogue entries are skills and instructions for workflows within Codeg.
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 xintaofei/codeg --skill citation-managementgit clone --depth 1 https://github.com/xintaofei/codegWrote 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/xintaofei/codeg/citation-management)<a href="https://agentmods.dev/skills/xintaofei/codeg/citation-management"><img src="https://agentmods.dev/badge/skills/xintaofei/codeg/citation-management/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/xintaofei/codeg/citation-management"><img src="https://agentmods.dev/badge/skills/xintaofei/codeg/citation-management.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00068 | $0.09866 |
| Opus 5.5 | $0.00027 | $0.03946 |
| Sonnet 5.5 | $0.00014 | $0.01973 |
| Haiku 4.5 | $0.00007 | $0.00987 |
Grade A, and why
citation-management 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 1mo 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.
This is a copy
91% identical to citation-management — 175 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 1,251 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Citation Management
Overview
Manage citations systematically throughout the research and writing process. This skill provides tools and strategies for searching academic databases (Google Scholar, PubMed), extracting accurate metadata from multiple sources (CrossRef, PubMed, arXiv), validating citation information, and generating properly formatted BibTeX entries.
Critical for maintaining citation accuracy, avoiding reference errors, and ensuring reproducible research. Integrates seamlessly with the literature-review skill for comprehensive research workflows.
When to Use This Skill
Use this skill when:
- Searching for specific papers on Google Scholar or PubMed
- Converting DOIs, PMIDs, or arXiv IDs to properly formatted BibTeX
- Extracting complete metadata for citations (authors, title, journal, year, etc.)
- Validating existing citations for accuracy
- Cleaning and formatting BibTeX files
- Finding highly cited papers in a specific field
- Verifying that citation information matches the actual publication
- Building a bibliography for a manuscript or thesis
- Checking for duplicate citations
- Ensuring consistent citation formatting
Visual Enhancement with Scientific Schematics
When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.
If your document does not already contain schematics or diagrams:
- Use the scientific-schematics skill to generate AI-powered publication-quality diagrams
- Simply describe your desired diagram in natural language
- Nano Banana Pro will automatically generate, review, and refine the schematic
For new documents: Scientific schematics should be generated by default to visually represent key concepts, workflows, architectures, or relationships described in the text.
How to generate schematics:
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
The AI will automatically:
- Create publication-quality images with proper formatting
- Review and refine through multiple iterations
- Ensure accessibility (colorblind-friendly, high contrast)
- Save outputs in the figures/ directory
What ships with it
15 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/bibtex_template.bib 9.0 KB
- assets/citation_checklist.md 10 KB
- references/bibtex_formatting.md 19 KB
- references/citation_validation.md 17 KB
- references/google_scholar_search.md 17 KB
- references/metadata_extraction.md 19 KB
- references/pubmed_search.md 17 KB
- scripts/doi_to_bibtex.py 6.2 KB runs code
- scripts/extract_metadata.py 20 KB runs code
- scripts/format_bibtex.py 11 KB runs code
- scripts/generate_schematic_ai.py 32 KB runs code
- scripts/generate_schematic.py 5.0 KB runs code
- scripts/search_google_scholar.py 8.8 KB runs code
- scripts/search_pubmed.py 13 KB runs code
- scripts/validate_citations.py 27 KB runs code
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.
- 1mo ago First seen · 1,251 lines · 68 tokens per session scan A f71c03433a2c
citation-management is a skill published in the GitHub repository xintaofei/codeg (4,087 stars, last pushed 3d ago), licensed Apache-2.0. It adds 68 tokens to every session and 9,866 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to citation-management, differing in 175 lines, and is treated as a copy.
Other skills, from other repositories
terminal
Use Desktop Commander for terminal and command-line work, especially anything that needs a shell whose state persists across turns: Python/Node REPLs, database shells, dev servers and other long-running processes, SSH into remote machines, and Windows PowerShell. Also handles everyday terminal tasks — navigating…
knowledge-base
Create and maintain a Markdown knowledge base that any AI agent can read, search, and update. Use when the user wants to start a knowledge base, add or update notes, organize docs/notes for an agent or LLM to consume, build an index of notes, or run a cleanup/maintenance pass on an existing MD knowledge base. Triggers…
obsidian-vault
Organize Obsidian vaults with MOCs, wikilinks, frontmatter/properties, dashboards, orphan-note checks, and cleanup workflows. Use ONLY when the user explicitly refers to Obsidian — by naming "Obsidian", an Obsidian "vault", or an Obsidian-specific feature such as wikilinks ("[[ ]]"), the Dataview or Bases plugins, or…
desktop-commander-overview
Use for Desktop Commander MCP capabilities — persistent shells and REPLs, long-running processes, filesystem beyond the workspace, structured files (.xlsx, .docx, .pdf, images) and large local data files such as CSVs, ripgrep search at scale, SSH, or cross-turn state.
ai-tools-setup
Set up, connect, validate, and repair Claude Desktop and MCP servers using Desktop Commander — inspecting and fixing mcp.json / claudedesktopconfig.json, getting MCP servers to connect, and diagnosing local AI tooling. Use when a user wants to install, configure, connect, validate, or fix Claude Desktop, an MCP…
computer-health-check
Run a comprehensive, read-only health check on the user's computer and return a scored chat summary with prioritized, plain-English recommendations and safe cleanup suggestions. Use this whenever the user wants to check their computer's health, speed it up, free up / reclaim disk space, find what's eating CPU / memory…