Academic Research
voidful/academic-skills
Complete academic research skill suite covering the full pipeline: paper reading (read/explain papers with storytelling), idea generation (brainstorm research directions), experiment design (plan…
Step 5 of the PaperOrchestra pipeline (arXiv:2604.05018). An agent skill from Ar9av/PaperOrchestra.
Install Content Refinement Agent
$ npx skills add Ar9av/PaperOrchestra --skill content-refinement-agent -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Ar9av/PaperOrchestra content-refinement-agent --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Ar9av/PaperOrchestra.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/content-refinement-agent .claude/skills/content-refinement-agent && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "content-refinement-agent" agent skill from https://github.com/Ar9av/PaperOrchestra/tree/main/skills/content-refinement-agent into .claude/skills/content-refinement-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "content-refinement-agent", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Ar9av/PaperOrchestra/tree/main/skills/content-refinement-agentType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Ar9av/PaperOrchestra --skill content-refinement-agent -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Ar9av/PaperOrchestra content-refinement-agent --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Ar9av/PaperOrchestra.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/content-refinement-agent .agents/skills/content-refinement-agent && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "content-refinement-agent" agent skill from https://github.com/Ar9av/PaperOrchestra/tree/main/skills/content-refinement-agent into .agents/skills/content-refinement-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "content-refinement-agent", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Ar9av/PaperOrchestra --skill content-refinement-agent -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Ar9av/PaperOrchestra content-refinement-agent --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Ar9av/PaperOrchestra.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/content-refinement-agent .cursor/skills/content-refinement-agent && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "content-refinement-agent" agent skill from https://github.com/Ar9av/PaperOrchestra/tree/main/skills/content-refinement-agent into .cursor/skills/content-refinement-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "content-refinement-agent", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Ar9av/PaperOrchestra.git --path skills/content-refinement-agent--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Ar9av/PaperOrchestra --skill content-refinement-agent -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Ar9av/PaperOrchestra content-refinement-agent --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Ar9av/PaperOrchestra.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/content-refinement-agent .gemini/skills/content-refinement-agent && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "content-refinement-agent" agent skill from https://github.com/Ar9av/PaperOrchestra/tree/main/skills/content-refinement-agent into .gemini/skills/content-refinement-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "content-refinement-agent", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Ar9av/PaperOrchestra content-refinement-agentInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Ar9av/PaperOrchestra --skill content-refinement-agent -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Ar9av/PaperOrchestra.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/content-refinement-agent .github/skills/content-refinement-agent && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "content-refinement-agent" agent skill from https://github.com/Ar9av/PaperOrchestra/tree/main/skills/content-refinement-agent into .github/skills/content-refinement-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "content-refinement-agent", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Ar9av/PaperOrchestra --skill content-refinement-agent -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Ar9av/PaperOrchestra content-refinement-agent --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Ar9av/PaperOrchestra.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/content-refinement-agent .opencode/skills/content-refinement-agent && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "content-refinement-agent" agent skill from https://github.com/Ar9av/PaperOrchestra/tree/main/skills/content-refinement-agent into .opencode/skills/content-refinement-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "content-refinement-agent", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
content-refinement-agent- GitHub stars
- 676
- Token cost
- ~4.9k tokens
- SKILL.md length
- 1,877 words
- Files
- 19 (incl. scripts, references)
- Skills in repo
- 9
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Step 5 of the PaperOrchestra pipeline (arXiv:2604.05018). An agent skill from Ar9av/PaperOrchestra.
- Works in 8 steps: Pre-refinement integrity gate → Simulate peer review → Score the draft → …
- The orchestrator delegates Step 5
- SKILL.md covers Inputs, Outputs, The refinement loop and Step-by-step, plus 2 more sections
- Runs Python scripts from its folder; calls python and python3
What it does
Content Refinement Agent is an agent skill from Ar9av/PaperOrchestra. Step 5 of the PaperOrchestra pipeline (arXiv:2604.05018). Iteratively refine drafts/paper.tex by simulating peer review and applying targeted revisions, with strict accept/revert halt rules, deterministic 0-100 decision bands (Accept/Minor/Major/Reject) that drive a target-met early stop, and a Devil's Advocate concession-threshold guard that blocks acceptance on unresolved critical findings. Maintains a worklog and snapshots each iteration so revert is real, not symbolic. TRIGGER when the orchestrator delegates…
Its SKILL.md is about 4.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 20 other files, including scripts and reference files (for example `references/ai-failure-modes.md`, `references/claim-evidence-map.md` and `references/da-reviewer.md`).
It sits in Research & Science, covering Academic paper search, LaTeX and Peer review. It works with arXiv. The repository describes itself as: An automated AI research-paper writer based off Google's PaperOrchestra paper's implementation through a skills - benchmark + autoraters using any coding agent (Claude Code…
When your agent uses it
- The orchestrator delegates Step 5
- The user asks to refine the draft
- Iterate on the paper
- Run peer review on this paper
Example prompts
- “refine the draft”
- “iterate on the paper”
- “run peer review on this paper”
- “/content-refinement-agent”
Requirements
- Python 3
Workflow steps
8 steps, taken from the step headings in SKILL.md.
- Pre-refinement integrity gate
- Simulate peer review
- Score the draft
- Apply revision
- Compile and re-score
- Apply the accept/revert decision
- Halt rules
- Promote the best snapshot
What it can do on your machine
Read from SKILL.md and the folder at commit 36c3cc4. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 9 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
pythonpython3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Content Refinement Agent loads about 4.9k tokens when it runs, and up to ~14k if it reads all its reference files. Until then it costs about 164 tokens; SKILL.md has 1,877 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 1,877 words (~4,896 tokens).
“Faithful implementation of the Content Refinement Agent from PaperOrchestra (Song et al., 2026, arXiv:2604.05018, §4 Step 5, App. F.1 pp. 49–51).”
- name
- content-refinement-agent
- data_access_level
- verified_only
Files
SKILL.md and 18 other files (scripts, references) in skills/content-refinement-agent of Ar9av/PaperOrchestra.
- SKILL.md
- references/ai-failure-modes.md
- references/claim-evidence-map.md
- references/da-reviewer.md
- references/halt-rules.md
- references/prompt.md
- references/reverse-outline.md
- references/reviewer-rubric.md
- references/safe-revision-rules.md
- references/writing-quality-check.md
- scripts/apply_worklog.py
- scripts/concession_guard.py
- scripts/decision_band.py
- scripts/reverse_outline.py
- scripts/score_delta.py
- scripts/score_trajectory.py
- scripts/snapshot.py
- scripts/test_reverse_outline.py
- scripts/update_critique_memory.py
Open the folder on GitHubat commit 36c3cc4
Compare with similar skills
Content Refinement Agent next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Content Refinement Agent this skillAr9av/PaperOrchestra | 676 | — | ~4.9k | Automated safety check: Pass | Custom licence | |
| Academic Researchvoidful/academic-skills | 132 | — | ~887 | Automated safety check: Pass | MIT | |
| Content Refinement Agentappleweiping/WEIPING_WIKI | 119 | — | ~3k | Automated safety check: Pass | MIT | |
| Arxiv PreflightMathews-Tom/armory | 327 | — | ~2k | Automated safety check: Pass | MIT | |
| Arxiv MCP Serverblazickjp/arxiv-mcp-server | 3.2k | — | ~353 | Automated safety check: Pass | Apache-2.0 | |
| Arxiv Paper Writerappautomaton/latex-arxiv-SKILL | 457 | — | ~2.3k | Automated safety check: Pass | MIT |
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Related
Works with
Categories
Questions about Content Refinement Agent
What does Content Refinement Agent do?
Step 5 of the PaperOrchestra pipeline (arXiv:2604.05018). An agent skill from Ar9av/PaperOrchestra. Content Refinement Agent is an agent skill from Ar9av/PaperOrchestra.05018).
When should I use Content Refinement Agent?
Content Refinement Agent fits situations like: the orchestrator delegates Step 5; the user asks to refine the draft; iterate on the paper; run peer review on this paper.
How do I install Content Refinement Agent in Claude Code?
Run `npx skills add Ar9av/PaperOrchestra --skill content-refinement-agent -a claude-code`. Or copy the skill folder (skills/content-refinement-agent in Ar9av/PaperOrchestra) into .claude/skills/content-refinement-agent in your project. Claude Code loads it when a task matches its description.
How do I install Content Refinement Agent in Codex?
Run `npx skills add Ar9av/PaperOrchestra --skill content-refinement-agent -a codex`. Or copy the skill folder (skills/content-refinement-agent in Ar9av/PaperOrchestra) into .agents/skills/content-refinement-agent in your project. Codex loads it when a task matches its description.
Can I use Content Refinement Agent in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Ar9av/PaperOrchestra --skill content-refinement-agent -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/content-refinement-agent, .gemini/skills/content-refinement-agent, .github/skills/content-refinement-agent and .opencode/skills/content-refinement-agent in your project.
What does Content Refinement Agent need to run?
Going by SKILL.md and its folder, Content Refinement Agent needs Python for the scripts in its folder and the command-line tools its instructions call (python and python3). Our summary lists: Python 3.
Does Content Refinement Agent access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Content Refinement Agent safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Content Refinement Agent use?
Content Refinement Agent has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Content Refinement Agent use?
About 4.9k tokens (SKILL.md is roughly 20k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 8.9k tokens, read only when the agent opens those files.
What are the alternatives to Content Refinement Agent?
Skills that share tags, products or a category with Content Refinement Agent: Academic Research (voidful/academic-skills, 132 stars), Content Refinement Agent (appleweiping/WEIPING_WIKI, 119 stars), Arxiv Preflight (Mathews-Tom/armory, 327 stars) and Arxiv MCP Server (blazickjp/arxiv-mcp-server, 3.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Content Refinement Agent?
Ar9av (a GitHub user) maintains it in Ar9av/PaperOrchestra, which has 676 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on September 21, 2026.
Source: Ar9av/PaperOrchestra on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.