Paper Labeler
PurCL/ASE
Extracts research papers from .bib and .html venue files, filters them by relevance, labels them with a two-level taxonomy through Claude and rebuilds a website.
End-to-end AI-assisted meta-analysis pipeline orchestration from TOPIC.txt to final manuscript and reviewer responses.
Install Ma End To End
$ npx skills add htlin222/meta-pipe --skill ma-end-to-end -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install htlin222/meta-pipe ma-end-to-end --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/htlin222/meta-pipe.git skills-src && mkdir -p .claude/skills && cp -r skills-src/ma-end-to-end .claude/skills/ma-end-to-end && 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 "ma-end-to-end" agent skill from https://github.com/htlin222/meta-pipe/tree/main/ma-end-to-end into .claude/skills/ma-end-to-end/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ma-end-to-end", 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/htlin222/meta-pipe/tree/main/ma-end-to-endType 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 htlin222/meta-pipe --skill ma-end-to-end -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install htlin222/meta-pipe ma-end-to-end --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/htlin222/meta-pipe.git skills-src && mkdir -p .agents/skills && cp -r skills-src/ma-end-to-end .agents/skills/ma-end-to-end && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ma-end-to-end" agent skill from https://github.com/htlin222/meta-pipe/tree/main/ma-end-to-end into .agents/skills/ma-end-to-end/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ma-end-to-end", 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 htlin222/meta-pipe --skill ma-end-to-end -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install htlin222/meta-pipe ma-end-to-end --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/htlin222/meta-pipe.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/ma-end-to-end .cursor/skills/ma-end-to-end && 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 "ma-end-to-end" agent skill from https://github.com/htlin222/meta-pipe/tree/main/ma-end-to-end into .cursor/skills/ma-end-to-end/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ma-end-to-end", 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/htlin222/meta-pipe.git --path ma-end-to-end--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 htlin222/meta-pipe --skill ma-end-to-end -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install htlin222/meta-pipe ma-end-to-end --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/htlin222/meta-pipe.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/ma-end-to-end .gemini/skills/ma-end-to-end && 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 "ma-end-to-end" agent skill from https://github.com/htlin222/meta-pipe/tree/main/ma-end-to-end into .gemini/skills/ma-end-to-end/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ma-end-to-end", 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 htlin222/meta-pipe ma-end-to-endInstalls 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 htlin222/meta-pipe --skill ma-end-to-end -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/htlin222/meta-pipe.git skills-src && mkdir -p .github/skills && cp -r skills-src/ma-end-to-end .github/skills/ma-end-to-end && 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 "ma-end-to-end" agent skill from https://github.com/htlin222/meta-pipe/tree/main/ma-end-to-end into .github/skills/ma-end-to-end/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ma-end-to-end", 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 htlin222/meta-pipe --skill ma-end-to-end -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install htlin222/meta-pipe ma-end-to-end --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/htlin222/meta-pipe.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/ma-end-to-end .opencode/skills/ma-end-to-end && 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 "ma-end-to-end" agent skill from https://github.com/htlin222/meta-pipe/tree/main/ma-end-to-end into .opencode/skills/ma-end-to-end/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ma-end-to-end", 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
ma-end-to-end- GitHub stars
- 139
- Token cost
- ~2.3k tokens
- SKILL.md length
- 842 words
- Files
- 17 (incl. scripts, references)
- Skills in repo
- 15
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
End-to-end AI-assisted meta-analysis pipeline orchestration from TOPIC.txt to final manuscript and reviewer responses.
- Works in 5 steps: Initialize Python tooling with uv inside… → Use uv add to manage dependencies for… → Run Python scripts via uv run (do not… → …
- The user provides a topic and wants the full meta-analysis workflow
- SKILL.md covers Overview, Inputs, Outputs and Project Layout (Numbered), plus 6 more sections
- Runs Python scripts from its folder; calls uv
What it does
Ma End To End is an agent skill from htlin222/meta-pipe. End-to-end AI-assisted meta-analysis pipeline orchestration from TOPIC.txt to final manuscript and reviewer responses. Use when the user provides a topic and wants the full meta-analysis workflow, tracking, and final paper.
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 18 other files, including scripts and reference files (for example `references/artifact-stamping.md`, `references/metadat-validation.md` and `references/resume-workflow.md`).
It sits in Research & Science, covering End-to-end testing and Data pipelines and ETL. It works with Python. The repository describes itself as: Claude Code-powered end-to-end meta-analysis automation: AI-assisted literature review, screening, extraction, analysis, and manuscript generation for systematic reviews and….
When your agent uses it
- The user provides a topic and wants the full meta-analysis workflow
- Tasks that involve End-to-end testing
- Tasks that involve Data pipelines and ETL
Example prompts
- “/ma-end-to-end”
Requirements
- Python 3
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Initialize Python tooling with uv inside tooling/python/ using uv init.
- Use uv add to manage dependencies for search and automation scripts.
- Run Python scripts via uv run (do not call python3 directly).
- Use uv tool for any external CLI helpers that should be isolated.
- Use R with renv inside 06_analysis/ for reproducible meta-analysis.
What it can do on your machine
Read from SKILL.md and the folder at commit 5c5c3f0. 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 10 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
uv
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.
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
Ma End To End loads about 2.3k tokens when it runs, and up to ~13k if it reads all its reference files. Until then it costs about 59 tokens; SKILL.md has 842 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 842 words (~2,337 tokens).
“Coordinate the complete meta-analysis workflow, ensure every step is tracked, and produce a final manuscript with reviewer responses.”
- name
- ma-end-to-end
Files
SKILL.md and 16 other files (scripts, references) in ma-end-to-end of htlin222/meta-pipe.
- SKILL.md
- references/artifact-stamping.md
- references/metadat-validation.md
- references/resume-workflow.md
- references/skill-generalization.md
- references/template-extraction-status.md
- references/time-guidance.md
- scripts/audit_screening_quality.py
- scripts/checkpoint.py
- scripts/final_qa_report.py
- scripts/hash_artifacts.py
- scripts/init_project.py
- scripts/publication_readiness_score.py
- scripts/run_robustness_checks.py
- scripts/validate_module_registry.py
- scripts/validate_pipeline.py
- scripts/validate_stage_transition.py
Open the folder on GitHubat commit 5c5c3f0
Compare with similar skills
Ma End To End 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 |
|---|---|---|---|---|---|---|
| Ma End To End this skillhtlin222/meta-pipe | 139 | — | ~2.3k | Automated safety check: Pass | Custom licence | |
| Paper LabelerPurCL/ASE | 637 | — | ~5.2k | Automated safety check: Warn | None | |
| GgetK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~2.8k | Automated safety check: Notes | BSD-2-Clause | |
| Research Workflow Automationwentorai/research-plugins | 298 | 1 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Authoritative Data Harvesteryushui2022/MathModel-Skill | 454 | 1 repos | ~1.1k | Automated safety check: Pass | MIT | |
| Web Application Testinganthropics/skills | 180k | 51 repos | ~966 | Automated safety check: Pass | Apache-2.0 |
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More from htlin222/meta-pipe
All 15 skills in this repoMa Data Extraction
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Define extraction schema, extract study data from full texts, and store it in a structured database for meta-analysis.
Ma Fulltext Management
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Collect and manage full-text PDFs for included studies, track provenance, and prepare documents for extraction.
Ma Screening Quality
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Perform title and abstract screening, apply inclusion and exclusion criteria, and assess study quality or risk of bias.
Ma Search Bibliography
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Conduct literature searches for meta-analysis using Python with uv, query PubMed and other databases, deduplicate results, and store round-based bibliographies with notes.
Ma Manuscript Quarto
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Draft and render a meta-analysis manuscript with Quarto using an IMRaD structure and embedded figures/tables.
Ma Meta Analysis
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Run statistical meta-analysis in R with renv, generate effect estimates, heterogeneity, and publication bias diagnostics, and export figures and tables.
Related
Works with
Categories
Questions about Ma End To End
What does Ma End To End do?
End-to-end AI-assisted meta-analysis pipeline orchestration from TOPIC.txt to final manuscript and reviewer responses. Ma End To End is an agent skill from htlin222/meta-pipe.txt to final manuscript and reviewer responses.
When should I use Ma End To End?
Ma End To End fits situations like: the user provides a topic and wants the full meta-analysis workflow; tasks that involve End-to-end testing; tasks that involve Data pipelines and ETL.
How do I install Ma End To End in Claude Code?
Run `npx skills add htlin222/meta-pipe --skill ma-end-to-end -a claude-code`. Or copy the skill folder (ma-end-to-end in htlin222/meta-pipe) into .claude/skills/ma-end-to-end in your project. Claude Code loads it when a task matches its description.
How do I install Ma End To End in Codex?
Run `npx skills add htlin222/meta-pipe --skill ma-end-to-end -a codex`. Or copy the skill folder (ma-end-to-end in htlin222/meta-pipe) into .agents/skills/ma-end-to-end in your project. Codex loads it when a task matches its description.
Can I use Ma End To End 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 htlin222/meta-pipe --skill ma-end-to-end -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ma-end-to-end, .gemini/skills/ma-end-to-end, .github/skills/ma-end-to-end and .opencode/skills/ma-end-to-end in your project.
What does Ma End To End need to run?
Going by SKILL.md and its folder, Ma End To End needs Python for the scripts in its folder and the command-line tools its instructions call (uv). Our summary lists: Python 3.
Does Ma End To End access the network?
SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Ma End To End 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 Ma End To End use?
Ma End To End 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 Ma End To End use?
About 2.3k tokens (SKILL.md is roughly 9.3k 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 10k tokens, read only when the agent opens those files.
What are the alternatives to Ma End To End?
Skills that share tags, products or a category with Ma End To End: Paper Labeler (PurCL/ASE, 637 stars), Gget (K-Dense-AI/scientific-agent-skills, 48k stars), Research Workflow Automation (wentorai/research-plugins, 298 stars) and Authoritative Data Harvester (yushui2022/MathModel-Skill, 454 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Ma End To End?
htlin222 (a GitHub user) maintains it in htlin222/meta-pipe, which has 139 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on September 23, 2026.
Source: htlin222/meta-pipe on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.