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Agent skill

Ai4s Agent

by ai4s-research in ai4s-research/ai4s-skills

A skill your agent uses when the user wants an end-to-end AI4S research pipeline — broad direction or specific topic in, full research package out (exploration + literature survey + experiment +…

MITAuto-check passedResearch & Science

Install Ai4s Agent

skills CLI
$ npx skills add ai4s-research/ai4s-skills --skill ai4s-agent -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ai4s-research/ai4s-skills ai4s-agent --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ai4s-research/ai4s-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai4s-agent .claude/skills/ai4s-agent && rm -rf skills-src

Use ~/.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/

Facts

Skill name
ai4s-agent
GitHub stars
237
Used in
1 other repo
Token cost
~1.6k tokens
SKILL.md length
592 words
Files
1
Skills in repo
7
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when the user wants an end-to-end AI4S research pipeline — broad direction or specific topic in, full research package out (exploration + literature survey + experiment +…

  • Works in 6 steps: Understand the user's starting point → Explore (only if input was a direction) → Literature survey → …
  • The user wants an end-to-end AI4S research pipeline — broad direction
  • SKILL.md covers Overview, When to use, When NOT to use and The slug contract, plus 3 more sections
  • Calls claude

What it does

Ai4s Agent is an agent skill from ai4s-research/ai4s-skills. Use when the user wants an end-to-end AI4S research pipeline — broad direction or specific topic in, full research package out (exploration + literature survey + experiment + paper). Meta-skill that chains the four downstream skills in order. Pure markdown, no Python runtime.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science. It works with Python. The repository describes itself as: Open-source agent skills for AI for Science: topic exploration, literature survey, experiments, paper writing, and integrity audit — driven by any coding agent. The licence is MIT.

When your agent uses it

  • The user wants an end-to-end AI4S research pipeline — broad direction
  • Specific topic in
  • Full research package out (exploration + literature survey + experiment + paper)

Example prompts

  • “/ai4s-agent”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Understand the user's starting point
  2. Explore (only if input was a direction)
  3. Literature survey
  4. Experiment package
  5. Paper
  6. Deliver

What it can do on your machine

Read from SKILL.md and the folder at commit 744ab20. 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

    Shell commands in SKILL.md call:

    • claude

    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

Ai4s Agent loads about 1.6k tokens when it runs. Until then it costs about 72 tokens; SKILL.md has 592 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~72
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from ai4s-research/ai4s-skills at commit 744ab20, republished under its MIT licence (© ai4s-research). 592 words, ~1,590 tokens.

Download SKILL.mdSave it as .claude/skills/ai4s-agent/SKILL.md (or your agent's skills folder).
name
ai4s-agent
description
Use when the user wants an end-to-end AI4S research pipeline — broad direction or specific topic in, full research package out (exploration + literature survey + experiment + paper). Meta-skill that chains the four downstream skills in order. Pure markdown, no Python runtime.

AI4S Agent (meta-skill)

Overview

Top-level entry point for the AI4S research stack. This skill contains no work of its own — its only job is to call four downstream skills in the right order, with the right slug, and reuse intermediate artifacts by path convention.

direction → research-explorer → topic
topic     → literature-survey  (60+ real bib, 100+ recommended)
topic     → experiment-suite   (design + code + results + figures)
topic     → paper-writer       (assembles into 200+ cite PDF)

Each downstream skill is already single-stage and self-sufficient: its agent loads that skill's SKILL.md and produces the full final-quality artifact directly. There is no skeleton/enrichment split. This meta-skill only handles ordering, the path convention, and disclosure consistency.

When to use

  • User asks for "a paper on X" or "research package on X" and wants the whole stack run end to end.
  • User wants to compare what each skill produces — useful for developing or debugging the pipeline itself.

When NOT to use

  • User wants to run only one stage (e.g. only the literature survey) → invoke that skill directly.
  • User wants only topic exploration → invoke research-explorer directly.

The slug contract

Every skill computes the same slug from the same topic string:

python
import re, hashlib
def slug(t):
    n = re.sub(r'[\s_]+', '-', re.sub(r'[^\w\s-]', '', t.lower().strip())).strip('-')[:40].rstrip('-')
    h = hashlib.sha1(t.encode()).hexdigest()[:8]
    return f"{n}-{h}"

Use the same string across all four skills. If the user provides a direction (not a topic), research-explorer runs against the direction; once a topic is chosen, the topic becomes the slug input for the remaining three.

Workflow

Step 1 — Understand the user's starting point
  • Direction ("transformer time series forecasting") — start at research-explorer, pick a topic from its research_exploration.md, then proceed.
  • Topic ("Transformer-based long-horizon forecasting with patch tokenisation") — skip research-explorer; go straight to the parallel branch (literature-survey, experiment-suite, paper-writer).
  • Real measured experiment data? If yes, the user supplies a results.json path; experiment-suite loads it instead of writing a simulated one, and the paper's \thanks drops the simulated clause.
Step 2 — Explore (only if input was a direction)

Load the research-explorer skill. Follow its 5 steps to produce:

output/research-explorer/<dir_slug>/latest/{research_exploration.md, topic_matrix.md, literature_pre_survey.md}

Discuss the candidate topics with the user. They pick one specific topic; that string becomes $TOPIC for the rest.

Step 3 — Literature survey

Load the literature-survey skill with $TOPIC. It produces:

output/literature-survey/<topic_slug>/latest/survey_paper/
├── main.pdf                    # the 6–20 page survey
├── main.tex
├── bibliography.bib            # 60+ real entries, 100+ recommended (URL-anchored)
├── sections/, figures/
output/literature-survey/<topic_slug>/latest/literature_table.md

The survey bibliography must pass the temporal profile selected by literature-survey; AI4S defaults to at least 60% from the current calendar year and previous two years.

Show full SKILL.md (245 more words)Show less
Step 4 — Experiment package

Load the experiment-suite skill with $TOPIC. It produces:

output/experiment-suite/<topic_slug>/latest/
├── experiment_design.md
├── experiment/                  # runnable model.py / data.py / train.py / evaluate.py
├── results.json                 # with "simulated" + "provenance"
├── figures/                     # publication-grade + manifest.json (basenames only)
└── experiment_report.md

If a real results path was provided in Step 1, the agent loads it here and results.json is flagged "simulated": false.

Step 5 — Paper

Load the paper-writer skill with $TOPIC. Its cross-skill conventions automatically pick up Steps 3 and 4:

  • Seeds bibliography.bib from output/literature-survey/<topic_slug>/latest/survey_paper/bibliography.bib, then expands it to 200+ inside paper-writer if needed.
  • Re-runs the paper-writer freshness gate after expansion; adding older foundational references must not silently make a fast-moving bibliography stale.
  • Reads numbers and provenance from output/experiment-suite/<topic_slug>/latest/results.json.
  • Copies/symlinks the publication-grade figures from output/experiment-suite/<topic_slug>/latest/figures/.

It produces:

output/paper-writer/<topic_slug>/latest/paper/
├── main.pdf                    # 8–14 pages, 200+ cites
├── main.tex
├── bibliography.bib
├── sections/, figures/
Step 6 — Deliver

Report the four output roots to the user:

  1. output/research-explorer/<dir_slug>/latest/ (if exploration ran)
  2. output/literature-survey/<topic_slug>/latest/
  3. output/experiment-suite/<topic_slug>/latest/
  4. output/paper-writer/<topic_slug>/latest/

Plus the paper-writer stats per its references/05-quality-gate.md report format.

Disclosure consistency

The same simulated flag must drive disclosure across all four artifacts:

  • experiment-suite/.../results.json → "simulated": true|false is the source of truth.
  • experiment-suite/.../experiment_report.md top-of-page disclosure must match.
  • paper-writer/.../main.tex \author{AI4S Agent\thanks{…}} must include the simulated clause iff results.json has "simulated": true.
  • The always-on human-review clause is mandatory in every case.

Rules

  • No LLM SDK in any skill, including this one. Pure markdown — SKILL.md only.
  • One slug per topic, computed identically across skills. The contract above is non-negotiable.
  • Never collapse the four skills into one agent run. Each skill's SKILL.md is the single source of truth for what counts as "done" for its artifact.
  • A non-interactive runner (e.g. claude --print headless) lives outside the skills. The skills stay pure.

© ai4s-research, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/ai4s-agent of ai4s-research/ai4s-skills.

Open the folder on GitHubat commit 744ab20

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in ai4s-research/ai4s-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Ai4s 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.

Ai4s Agent compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Ai4s Agent this skillai4s-research/ai4s-skills2371 repos~1.6kAutomated safety check: PassMIT
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Neuropixels Data Analysisdavila7/claude-code-templates33k9 repos~2.8kAutomated safety check: PassMIT
High Stakes Analytics Decision Lablimingrui679-design/high-stakes-analytics-decision-lab1k—~2.2kAutomated safety check: PassMIT
Qiskit 2.x Quantum ML Referenceaiming-lab/AutoResearchClaw15k—~4.7kAutomated safety check: PassMIT
Modeling Code and Result Contractsyushui2022/MathModel-Skill454—~1.4kAutomated safety check: PassMIT

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Works with

Categories

Questions about Ai4s Agent

What does Ai4s Agent do?

A skill your agent uses when the user wants an end-to-end AI4S research pipeline — broad direction or specific topic in, full research package out (exploration + literature survey + experiment +…. Ai4s Agent is an agent skill from ai4s-research/ai4s-skills. Use when the user wants an end-to-end AI4S research pipeline — broad direction or specific topic in, full research package out (exploration + literature survey + experiment + paper).

When should I use Ai4s Agent?

Ai4s Agent fits situations like: the user wants an end-to-end AI4S research pipeline — broad direction; specific topic in; full research package out (exploration + literature survey + experiment + paper).

How do I install Ai4s Agent in Claude Code?

Run `npx skills add ai4s-research/ai4s-skills --skill ai4s-agent -a claude-code`. Or copy the skill folder (skills/ai4s-agent in ai4s-research/ai4s-skills) into .claude/skills/ai4s-agent in your project. Claude Code loads it when a task matches its description.

How do I install Ai4s Agent in Codex?

Run `npx skills add ai4s-research/ai4s-skills --skill ai4s-agent -a codex`. Or copy the skill folder (skills/ai4s-agent in ai4s-research/ai4s-skills) into .agents/skills/ai4s-agent in your project. Codex loads it when a task matches its description.

Can I use Ai4s 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 ai4s-research/ai4s-skills --skill ai4s-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/ai4s-agent, .gemini/skills/ai4s-agent, .github/skills/ai4s-agent and .opencode/skills/ai4s-agent in your project.

What does Ai4s Agent need to run?

Going by SKILL.md and its folder, Ai4s Agent needs the command-line tools its instructions call (claude). Our summary lists: Python 3.

Does Ai4s 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 Ai4s 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. Review the folder before installing.

What licence does Ai4s Agent use?

Ai4s Agent is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ai4s Agent use?

About 1.6k tokens (SKILL.md is roughly 6.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Ai4s Agent?

Skills that share tags, products or a category with Ai4s Agent: Nature-Style Scientific Figures (Yuan1z0825/nature-skills, 47k stars), Neuropixels Data Analysis (davila7/claude-code-templates, 33k stars), High Stakes Analytics Decision Lab (limingrui679-design/high-stakes-analytics-decision-lab, 1k stars) and Qiskit 2.x Quantum ML Reference (aiming-lab/AutoResearchClaw, 15k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ai4s Agent?

ai4s-research (a GitHub organization) maintains it in ai4s-research/ai4s-skills, which has 237 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on July 28, 2026.

Source: ai4s-research/ai4s-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.