Agent skill

Aim Experiment Guide

by wentorai in wentorai/research-plugins

Track and compare research experiments with Aim experiment tracker

MITAuto-check passed

Install Aim Experiment Guide

skills CLI

$ npx skills add wentorai/research-plugins --skill aim-experiment-guide -a claude-code

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

GitHub CLI

$ gh skill install wentorai/research-plugins aim-experiment-guide --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/wentorai/research-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/research/automation/aim-experiment-guide .claude/skills/aim-experiment-guide && 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/

Paste into Claude Code

Install the "aim-experiment-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/research/automation/aim-experiment-guide into .claude/skills/aim-experiment-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aim-experiment-guide", 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

$skill-installer install https://github.com/wentorai/research-plugins/tree/main/skills/research/automation/aim-experiment-guide

Type 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.

skills CLI

$ npx skills add wentorai/research-plugins --skill aim-experiment-guide -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install wentorai/research-plugins aim-experiment-guide --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/research/automation/aim-experiment-guide .agents/skills/aim-experiment-guide && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "aim-experiment-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/research/automation/aim-experiment-guide into .agents/skills/aim-experiment-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aim-experiment-guide", 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.

skills CLI

$ npx skills add wentorai/research-plugins --skill aim-experiment-guide -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install wentorai/research-plugins aim-experiment-guide --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/research/automation/aim-experiment-guide .cursor/skills/aim-experiment-guide && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "aim-experiment-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/research/automation/aim-experiment-guide into .cursor/skills/aim-experiment-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aim-experiment-guide", 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

$ gemini skills install https://github.com/wentorai/research-plugins.git --path skills/research/automation/aim-experiment-guide

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add wentorai/research-plugins --skill aim-experiment-guide -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install wentorai/research-plugins aim-experiment-guide --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/research/automation/aim-experiment-guide .gemini/skills/aim-experiment-guide && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "aim-experiment-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/research/automation/aim-experiment-guide into .gemini/skills/aim-experiment-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aim-experiment-guide", 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.

GitHub CLI

$ gh skill install wentorai/research-plugins aim-experiment-guide

Installs 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).

skills CLI

$ npx skills add wentorai/research-plugins --skill aim-experiment-guide -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/research/automation/aim-experiment-guide .github/skills/aim-experiment-guide && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "aim-experiment-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/research/automation/aim-experiment-guide into .github/skills/aim-experiment-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aim-experiment-guide", 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.

skills CLI

$ npx skills add wentorai/research-plugins --skill aim-experiment-guide -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install wentorai/research-plugins aim-experiment-guide --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/research/automation/aim-experiment-guide .opencode/skills/aim-experiment-guide && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "aim-experiment-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/research/automation/aim-experiment-guide into .opencode/skills/aim-experiment-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aim-experiment-guide", 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: aim-experiment-guide
GitHub stars: 298
Used in: 1 other repo
Token cost: ~1.9k tokens
SKILL.md length: 481 words
Files: 1
Skills in repo: 405
Repo updated: Jun 19, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Track and compare research experiments with Aim experiment tracker

SKILL.md covers Overview, Installation and Setup, Core Features and Research Workflow Integration, plus 2 more sections
Calls pip

What it does

Aim Experiment Guide is an agent skill from wentorai/research-plugins. Track and compare research experiments with Aim experiment tracker

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: 350+ academic research skills, MCP configs, and plugins for Research-Claw and AI agents. The licence is MIT.

Example prompts

“/aim-experiment-guide”

Requirements

Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit bf44b3c. 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:
- pip
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
- github.com
- aimstack.readthedocs.io
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

Aim Experiment Guide loads about 1.9k tokens when it runs. Until then it costs about 22 tokens; SKILL.md has 481 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~22
When it runs · the whole SKILL.md, loaded when a task matches: ~1.9k

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 wentorai/research-plugins at commit bf44b3c, republished under its MIT licence (© wentorai). 481 words, ~1,901 tokens.

Download SKILL.mdSave it as .claude/skills/aim-experiment-guide/SKILL.md (or your agent's skills folder).

name: aim-experiment-guide
description: Track and compare research experiments with Aim experiment tracker

Aim Experiment Tracker Guide

Overview

Aim is an open-source experiment tracking platform designed for researchers and ML engineers who need to log, compare, and analyze large numbers of experiments. Unlike cloud-based tracking services that require sending data to external servers, Aim runs entirely on your own infrastructure, making it suitable for research environments with data privacy requirements or institutional restrictions on external services.

The core problem Aim solves is experiment management at scale. A typical research project involves hundreds or thousands of training runs with different hyperparameters, data splits, model architectures, and random seeds. Without systematic tracking, researchers lose track of which configurations produced which results, leading to wasted computation and unreproducible findings. Aim provides a high-performance storage backend and a rich web UI for logging, querying, and visualizing experiment metadata and metrics.

With over 6,000 GitHub stars, Aim has established itself as a compelling self-hosted alternative to tools like Weights and Biases and MLflow. Its Python-native API integrates with minimal friction into existing training loops, and the query language enables sophisticated filtering across thousands of runs.

Installation and Setup

Install Aim via pip:

bash

pip install aim

Initialize an Aim repository in your project directory:

bash

cd /path/to/research-project
aim init

This creates a .aim directory that stores all experiment data locally. Launch the web UI:

bash

aim up

The dashboard becomes available at http://localhost:43800, providing interactive visualizations of all tracked experiments.

For remote server deployment:

bash

aim up --host 0.0.0.0 --port 43800

Core Features

Experiment Logging: Integrate Aim tracking into your training scripts with minimal code changes:

python

from aim import Run

# Initialize a tracked run
run = Run(experiment="protein_folding_v2")

# Log hyperparameters
run["hparams"] = {
    "learning_rate": 0.001,
    "batch_size": 64,
    "model": "transformer",
    "num_layers": 6,
    "hidden_dim": 256,
    "dropout": 0.1,
    "optimizer": "adamw",
    "weight_decay": 0.01,
    "seed": 42,
}

# Log dataset information
run["dataset"] = {
    "name": "protein_benchmark_v3",
    "train_size": 50000,
    "val_size": 5000,
    "test_size": 5000,
}

# Track metrics during training
for epoch in range(num_epochs):
    train_loss = train_one_epoch(model, train_loader)
    val_loss, val_accuracy = evaluate(model, val_loader)

    run.track(train_loss, name="loss", context={"subset": "train"})
    run.track(val_loss, name="loss", context={"subset": "val"})
    run.track(val_accuracy, name="accuracy", context={"subset": "val"})

Framework Integrations: Aim provides built-in callbacks for popular training frameworks:

python

# PyTorch Lightning integration
from aim.pytorch_lightning import AimLogger

aim_logger = AimLogger(experiment="lightning_exp")
trainer = pl.Trainer(logger=aim_logger, max_epochs=100)

# Hugging Face Transformers integration
from aim.hugging_face import AimCallback

aim_callback = AimCallback(experiment="hf_training")
trainer = Trainer(
    model=model,
    args=training_args,
    callbacks=[aim_callback],
)

# Keras integration
from aim.keras import AimCallback as KerasAimCallback

model.fit(
    x_train, y_train,
    callbacks=[KerasAimCallback(experiment="keras_exp")],
    epochs=50,
)

Powerful Query Language: Filter and retrieve experiments programmatically:

python

from aim import Repo

repo = Repo("/path/to/research-project")

# Query runs matching specific criteria
query = """
run.experiment == "protein_folding_v2"
and run.hparams.learning_rate < 0.01
and run.hparams.model == "transformer"
"""

for run in repo.query_runs(query).iter_runs():
    print(f"Run: {run.hash}")
    print(f"  LR: {run['hparams']['learning_rate']}")
    print(f"  Final val loss: {run['loss']}")

Rich Visualizations: The web UI provides interactive charts for comparing experiments:

Line charts for metric trajectories across epochs
Parallel coordinates plots for hyperparameter exploration
Scatter plots correlating hyperparameters with final metrics
Distribution plots for metric analysis across run groups
Image and audio tracking for multimedia experiments

Show full SKILL.md (178 more words)Show less

Research Workflow Integration

Hyperparameter Search Analysis: After running grid search or random search experiments, use Aim to identify the best configurations:

python

from aim import Repo

repo = Repo(".")

# Find the best run by validation accuracy
best_run = None
best_acc = 0.0

for run_metrics in repo.query_metrics(
    "metric.name == 'accuracy' and metric.context.subset == 'val'"
).iter_runs():
    for metric in run_metrics:
        final_val = list(metric.values.values())[-1]
        if final_val > best_acc:
            best_acc = final_val
            best_run = metric.run.hash

print(f"Best run: {best_run} with accuracy {best_acc:.4f}")

Reproducibility Documentation: Every tracked run captures the full hyperparameter configuration, making it straightforward to include exact experimental details in paper methods sections and supplementary materials.

Ablation Studies: Tag runs with ablation group identifiers and use the comparison UI to visualize the impact of each component:

python

run = Run(experiment="ablation_study")
run["hparams"] = config
run["ablation"] = {
    "group": "attention_mechanism",
    "variant": "multi_head",
    "description": "Standard multi-head attention vs. linear attention",
}

Lab Notebook Integration: Export experiment summaries for inclusion in electronic lab notebooks. The query API enables automated report generation:

python

import pandas as pd
from aim import Repo

repo = Repo(".")
records = []

for run_metrics in repo.query_metrics(
    "metric.name == 'accuracy'"
).iter_runs():
    run = run_metrics.run
    for metric in run_metrics:
        values = list(metric.values.values())
        records.append({
            "run_hash": run.hash[:8],
            "model": run["hparams"].get("model"),
            "lr": run["hparams"].get("learning_rate"),
            "final_accuracy": values[-1] if values else None,
        })

df = pd.DataFrame(records)
df.to_csv("experiment_summary.csv", index=False)

Storage and Performance

Aim uses a custom high-performance storage engine optimized for time-series metrics data. The storage scales to millions of tracked values across thousands of runs without significant degradation in query performance.

Data is stored locally in the .aim directory. Back up this directory to preserve your experiment history. For team settings, the Aim server can be deployed as a shared service accessible to multiple researchers.

bash

# Check storage usage
du -sh .aim/

# Export data for archival
aim storage --repo . upgrade 3.0

References

Aim repository: https://github.com/aimhubio/aim
Aim documentation: https://aimstack.readthedocs.io/
Aim UI demo and screenshots in the repository wiki
Comparison with MLflow and Weights and Biases in the documentation

Files

Just SKILL.md in skills/research/automation/aim-experiment-guide of wentorai/research-plugins.

Open the folder on GitHubat commit bf44b3c

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 wentorai/research-plugins, which our catalogue first saw on October 7, 2026.

brycewang-stanford/Auto-Empirical-Research-Skillsskills/43-wentorai-research-plugins/skills/research/automation/aim-experiment-guide

Compare with similar skills

Aim Experiment Guide 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.

Aim Experiment Guide compared with similar skills
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Finding ExperimentsPostHog/posthog	40k	—	~826	Automated safety check: Pass	Custom licence	today
Arize Experimentgithub/awesome-copilot	40k	1 repos	~4.6k	Automated safety check: Notes	MIT	today
Experiment Trackerymx10086/ResearchClaw	312	—	~213	Automated safety check: Pass	Custom licence	6 mo ago

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Questions about Aim Experiment Guide

What does Aim Experiment Guide do?

Track and compare research experiments with Aim experiment tracker. Aim Experiment Guide is an agent skill from wentorai/research-plugins.

How do I install Aim Experiment Guide in Claude Code?

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

How do I install Aim Experiment Guide in Codex?

Run `npx skills add wentorai/research-plugins --skill aim-experiment-guide -a codex`. Or copy the skill folder (skills/research/automation/aim-experiment-guide in wentorai/research-plugins) into .agents/skills/aim-experiment-guide in your project. Codex loads it when a task matches its description.

Can I use Aim Experiment Guide 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 wentorai/research-plugins --skill aim-experiment-guide -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aim-experiment-guide, .gemini/skills/aim-experiment-guide, .github/skills/aim-experiment-guide and .opencode/skills/aim-experiment-guide in your project.

What does Aim Experiment Guide need to run?

Going by SKILL.md and its folder, Aim Experiment Guide needs the command-line tools its instructions call (pip). Our summary lists: Python 3.

Does Aim Experiment Guide access the network?

SKILL.md names 2 domains. As links in the text: github.com and aimstack.readthedocs.io. This is read from the text; nothing was executed.

Is Aim Experiment Guide 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 Aim Experiment Guide use?

Aim Experiment Guide 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 Aim Experiment Guide use?

About 1.9k tokens (SKILL.md is roughly 7.6k 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 Aim Experiment Guide?

Skills that share tags, products or a category with Aim Experiment Guide: Experiments (Arize-ai/phoenix, 12k stars), Experiment Detail Comparator (aipoch/medical-research-skills, 2k stars), Finding Experiments (PostHog/posthog, 40k stars) and Arize Experiment (github/awesome-copilot, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Aim Experiment Guide?

wentorai (a GitHub user) maintains it in wentorai/research-plugins, which has 298 GitHub stars. The repository holds 405 skills in this directory. The repository was last updated on June 19, 2026.

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

Aim Experiment Guide

Install Aim Experiment Guide

Facts

At a glance

What it does

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Aim Experiment Tracker Guide

Overview

Installation and Setup

Core Features

Research Workflow Integration

Storage and Performance

References

Files

Used in 1 other repository

Compare with similar skills

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Experiment Detail Comparator

Finding Experiments

Arize Experiment

Experiment Tracker

Scroll Experience

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Questions about Aim Experiment Guide