agentleFS
shimo4228shimo4228/claude-skill-paper-ecosystem/llms-full.txt

claude-skill-paper-ecosystem

llms.txt1 starsChanged 3 months agoMITView on GitHub

Self-contained reference for AI agents and LLM-based search systems. claude-skill-paper-ecosystem is a Claude Code Agent Skill bundle (MIT, v0.1.0) by Tatsuya Shimomoto (@shimo4228) for writing and reviewing academic papers. It bundles two skills and five reviewer subagents that install together. claude-skill-paper-ecosystem is defined as a bundle that packages the academic-paper write/review workflow as one installable unit: the paper-ecosystem orchestrator skill, the paper-writing draft skill, and five reviewer subagents (paper-reviewer, source-fidelity-checker, vocabulary-consistency-checker, clarity-reviewer, citation-formatter). It targets position papers, preprints, and journal-style…

The file

We split this llms-full.txt into the rules it gives an agent

1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Not for human-facing blog posts, essays, or newsletters — use claude-skill-writing-ecosystem.

    line 38

≈ “Common” is an estimate: at least 1 in 5 of the 3,592 llms.txt files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
llms-full.txt
# claude-skill-paper-ecosystem — Full AI Reference

> Self-contained reference for AI agents and LLM-based search systems. `claude-skill-paper-ecosystem` is a Claude Code Agent Skill bundle (MIT, v0.1.0) by Tatsuya Shimomoto (@shimo4228) for writing and reviewing academic papers. It bundles two skills and five reviewer subagents that install together.

## Project Facts

- **Name**: claude-skill-paper-ecosystem
- **Type**: Claude Code Agent Skill bundle (orchestrator skill + draft skill + 5 subagents)
- **Author**: Tatsuya Shimomoto (@shimo4228)
- **License**: MIT
- **Version**: 0.1.0 (initial public release, 2026-06-08)
- **Runtime deps**: none (documentation-only skills)
- **Status**: active; `skills/` and `agents/` are copied one way from the author's paper workspace (`scripts/sync-from-local.sh`, maintainer-only), so this copy can trail it between syncs
- **Parent project**: serves the papers of the Authorship Strategy project (concept DOI 10.5281/zenodo.20263316); the bundle itself has no DOI. Author hub: https://github.com/shimo4228/shimo4228
- **Counterparts**: claude-skill-writing-ecosystem (human-facing), llms-txt-writer (AI-facing)
- **Compatibility**: Designed for Claude Code (subagents are Claude-Code-specific; the SKILL.md format itself is the open Agent Skills standard)
- **Models**: `opus` for paper-reviewer and source-fidelity-checker, `sonnet` for the other three agents
- **Language**: the two SKILL.md files are written in Japanese with English technical terms; the agent definitions are mostly English

## What is claude-skill-paper-ecosystem?

claude-skill-paper-ecosystem is defined as a bundle that packages the academic-paper write/review workflow as one installable unit: the `paper-ecosystem` orchestrator skill, the `paper-writing` draft skill, and five reviewer subagents (paper-reviewer, source-fidelity-checker, vocabulary-consistency-checker, clarity-reviewer, citation-formatter). It targets position papers, preprints, and journal-style articles for SSRN, arXiv, Zenodo, and journal venues.

## Why does this repo bundle agents, when other skill repos do not?

The five reviewer subagents read their canonical rules from the `paper-ecosystem` skill at `~/.claude/skills/paper-ecosystem/SKILL.md`. A reviewer installed without that skill would reference missing rule sections and review incorrectly. So the skill and its agents must be installed together — which is what this repo packages, via `install.sh`. Agent Skills (SKILL.md) are an open cross-tool standard adopted by Codex, Gemini CLI, Cursor, and others; Claude Code *subagents* are not part of that standard, so a repo that bundles subagents is Claude-Code-specific.

## How do I install it?

Three ways. (1) One command: `git clone` then `./install.sh`, which copies every `skills/*` into `~/.claude/skills/`, every `agents/*.md` into `~/.claude/agents/`, runs `uv sync` for any skill with a `pyproject.toml`, and moves a pre-existing skill folder or agent file that differs to `~/.claude/backups/install-<timestamp>/` before copying (flags: `--force` skips backups, `--dry-run` shows what would change). (2) Manual: `cp -r` each skill into `~/.claude/skills/` and `cp agents/*.md ~/.claude/agents/`. (3) SkillsMP `/skills add shimo4228/claude-skill-paper-ecosystem` — but this installs `skills/` only, not `agents/`, so the agents must then be copied manually.

## What is the write-review-deposit flow?

First, draft with `paper-writing`: establish the primary-source list, then draft section by section while holding a claim↔cite 1:1 mapping. Second, review in parallel with paper-reviewer (argument flow, claim sharpness, missing or misaligned cite pointers), source-fidelity-checker (claim vs primary source), vocabulary-consistency-checker (term definitions), and clarity-reviewer (first-contact reader). Third, run citation-formatter last as the final gate (reference apparatus, DOI/arXiv validity). Deposit is a separate stage handled outside this repo (`release-doi` for repo-level Zenodo deposits; `paper-writing` hands paper-level deposits to a `paper-deposit` skill that this repo does not include). The reviewers only report; none of them edits the paper.

## When should this bundle NOT be used?

Not for human-facing blog posts, essays, or newsletters — use claude-skill-writing-ecosystem. Not for AI-facing documents such as llms.txt, FAQ, or glossary — use llms-txt-writer. Not for human-facing READMEs — use readme-writer.

## What are the canonical rules the orchestrator holds?

The `paper-ecosystem` skill is the single source of truth for five rule sets that the draft skill and the reviewer agents inherit: Source Fidelity Rules (claims must reflect the cited primary source, not a drifted glossary), Vocabulary Consistency Rules (terms keep one definition; sub-classifications explicit at introduction), Academic Voice Rules (AI-slop ban, register), Reader Clarity Rules (coined-term budget, no insider context), and Citation Format Rules (in-text ↔ reference 1:1, DOI/arXiv validity).

## Sibling skills

- claude-skill-writing-ecosystem: human-facing writing & review — also bundles its six review agents
- llms-txt-writer: AI-facing documents (llms.txt / llms-full.txt / FAQ / glossary)
- readme-writer: human-facing READMEs
- release-doi: repo-level Zenodo deposit (https://github.com/shimo4228/release-doi)
- Author hub (five practice lines, their DOIs, and the author's tools): https://github.com/shimo4228/shimo4228

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.