Iron Proxy Gateway for NanoClaw
nanocoai/nanoclaw
Installs or refreshes Iron Proxy and its Iron Control web console for NanoClaw, with a local Docker setup, database, credentials and a human approval bridge.
Prepare and orchestrate the complete local Docker evaluation for Active-SWE.
Install Active Swe Eval
$ npx skills add XLearning-SCU/Active-SWE --skill active-swe-eval -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install XLearning-SCU/Active-SWE active-swe-eval --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/XLearning-SCU/Active-SWE.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.codex/skills/active-swe-eval .claude/skills/active-swe-eval && 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 "active-swe-eval" agent skill from https://github.com/XLearning-SCU/Active-SWE/tree/main/.codex/skills/active-swe-eval into .claude/skills/active-swe-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "active-swe-eval", 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/XLearning-SCU/Active-SWE/tree/main/.codex/skills/active-swe-evalType 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 XLearning-SCU/Active-SWE --skill active-swe-eval -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install XLearning-SCU/Active-SWE active-swe-eval --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/XLearning-SCU/Active-SWE.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.codex/skills/active-swe-eval .agents/skills/active-swe-eval && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "active-swe-eval" agent skill from https://github.com/XLearning-SCU/Active-SWE/tree/main/.codex/skills/active-swe-eval into .agents/skills/active-swe-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "active-swe-eval", 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 XLearning-SCU/Active-SWE --skill active-swe-eval -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install XLearning-SCU/Active-SWE active-swe-eval --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/XLearning-SCU/Active-SWE.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.codex/skills/active-swe-eval .cursor/skills/active-swe-eval && 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 "active-swe-eval" agent skill from https://github.com/XLearning-SCU/Active-SWE/tree/main/.codex/skills/active-swe-eval into .cursor/skills/active-swe-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "active-swe-eval", 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/XLearning-SCU/Active-SWE.git --path .codex/skills/active-swe-eval--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 XLearning-SCU/Active-SWE --skill active-swe-eval -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install XLearning-SCU/Active-SWE active-swe-eval --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/XLearning-SCU/Active-SWE.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.codex/skills/active-swe-eval .gemini/skills/active-swe-eval && 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 "active-swe-eval" agent skill from https://github.com/XLearning-SCU/Active-SWE/tree/main/.codex/skills/active-swe-eval into .gemini/skills/active-swe-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "active-swe-eval", 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 XLearning-SCU/Active-SWE active-swe-evalInstalls 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 XLearning-SCU/Active-SWE --skill active-swe-eval -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/XLearning-SCU/Active-SWE.git skills-src && mkdir -p .github/skills && cp -r skills-src/.codex/skills/active-swe-eval .github/skills/active-swe-eval && 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 "active-swe-eval" agent skill from https://github.com/XLearning-SCU/Active-SWE/tree/main/.codex/skills/active-swe-eval into .github/skills/active-swe-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "active-swe-eval", 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 XLearning-SCU/Active-SWE --skill active-swe-eval -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install XLearning-SCU/Active-SWE active-swe-eval --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/XLearning-SCU/Active-SWE.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.codex/skills/active-swe-eval .opencode/skills/active-swe-eval && 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 "active-swe-eval" agent skill from https://github.com/XLearning-SCU/Active-SWE/tree/main/.codex/skills/active-swe-eval into .opencode/skills/active-swe-eval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "active-swe-eval", 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
active-swe-eval- GitHub stars
- 102
- Token cost
- ~938 tokens
- SKILL.md length
- 455 words
- Files
- 3
- Skills in repo
- 2
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Prepare and orchestrate the complete local Docker evaluation for Active-SWE.
- DevOps & Cloud work in your project
- Calls git and python; reaches huggingface.co
What it does
Active Swe Eval is an agent skill from XLearning-SCU/Active-SWE. Prepare and orchestrate the complete local Docker evaluation for Active-SWE. Claude Code remains the fixed executor for Recorded, Potential, and Judge.
Its SKILL.md is about 940 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `ENVIRONMENT.md` and `EVALUATION.md`).
It sits in DevOps & Cloud. It works with Docker. The repository describes itself as: Pytorch Implementation of Active-SWE: Benchmarking Coding Agents for Proactive Bug Fixing without Issue Reports. The licence is Apache-2.0.
When your agent uses it
- DevOps & Cloud work in your project
Example prompts
- “/active-swe-eval”
Requirements
- Python 3
- Docker
What it can do on your machine
Read from SKILL.md and the folder at commit 25ecfa5. 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:
gitpython
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
huggingface.co
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
Active Swe Eval loads about 938 tokens when it runs. Until then it costs about 42 tokens; SKILL.md has 455 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: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NoteMentions a .env fileSKILL.md:42
y_env` loaded from project-local `config/.env` or the - NoteMentions a .env fileSKILL.md:44
issing, ask the user to populate `config/.env`
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 XLearning-SCU/Active-SWE at commit 25ecfa5, republished under its Apache-2.0 licence (© XLearning-SCU). 455 words, ~938 tokens.
Download SKILL.mdSave it as
.claude/skills/active-swe-eval/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- active-swe-eval
- description
- Prepare and orchestrate the complete local Docker evaluation for Active-SWE. Claude Code remains the fixed executor for Recorded, Potential, and Judge.
Active-SWE Evaluation With Codex
Use this skill when Codex organizes Active-SWE on the host. Claude Code remains the fixed executor inside every task container.
Locate the project
First look for an existing project root containing both pyproject.toml and
the active_swe/ package. Reuse it without pulling, resetting, or replacing
local files. If no checkout exists, clone into a new relative workspace and
enter it:
git clone --depth 1 https://github.com/XLearning-SCU/Active-SWE.git Active-SWE
cd Active-SWEDo not clone over a non-empty path. If Git or repository access is unavailable,
stop and ask the user for an existing checkout. After locating or cloning the
project, open .codex/skills/active-swe-eval/SKILL.md from that checkout and
use the local copy as the authority for all remaining steps. Then read its
local ENVIRONMENT.md and EVALUATION.md; do not continue from an older remote
or cached copy of the skill.
Public sources are:
Source code: https://github.com/XLearning-SCU/Active-SWE
Dataset: https://huggingface.co/datasets/XLearning-SCU/Active-SWECheck config/evaluation.json. If absent, copy config/evaluation.example.json
and config/.env.example, then ask for missing values without silently
overwriting files. One task JSON contains evaluation_models, exactly one
judge_model, plus input, output, and host-side execution settings; keep
multiple tasks as separate JSON files. A
credential may use api_key_env loaded from project-local config/.env or the
host environment; a permission-restricted api_key_file remains available.
If a referenced variable is missing, ask the user to populate config/.env
without sending the value in chat. Hidden input is only for a user launching
the controller directly in an interactive terminal. Models run sequentially;
per-model concurrency defaults to 4, maximum turns to 300, and timeout to 5,400
seconds per task. Never put an API-key value in chat, models.json, or a
command line.
When the user selects only part of the configured models, pass one
--only-model ID per selection; keep the full config intact.
When the user identifies an existing task JSON and dotenv file, reuse them with
--config and --env-file.
Show full SKILL.md (164 more words)Show less
Use the public controller from the active_swe package:
python -m active_swe.run_evaluation \
--config config/evaluation.jsonCheck standard local Docker and Claude Code, download the requested public
dataset configuration to
data/Active-SWE.parquet, convert it to data/Active-SWE.jsonl, copy the exact
run input below <output.root>/<id>/<timestamp>/inputs/, pull and validate
referenced images, review the preflight image report, then
run Recorded and Potential with each evaluation model, Judge with the same
selected fixed judge, then metrics. The task's input.limit controls the
default scope; pass --limit N only for an intentional one-run override. The
materialized input is also the exact source used to choose preflight images.
Project-local tools belong under ./.tools; run artifacts belong under
./runs.
Recorded and Potential use Docker --network none; only their bundled
fixed-destination API tunnel may carry model traffic. Judge has a separate
network setting and retains host-network behavior. Report artifacts using
paths, stage outcome counts, and metrics relative to the run root, without
exposing credentials, endpoint details, or host paths. Treat controller ok
as pipeline completion, not proof that every sample produced all artifacts.
© XLearning-SCU, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 2 other files in .codex/skills/active-swe-eval of XLearning-SCU/Active-SWE.
- SKILL.md
- ENVIRONMENT.md
- EVALUATION.md
Open the folder on GitHubat commit 25ecfa5
Compare with similar skills
Active Swe Eval 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 |
|---|---|---|---|---|---|---|
| Active Swe Eval this skillXLearning-SCU/Active-SWE | 102 | — | ~938 | Automated safety check: Notes | Apache-2.0 | |
| Iron Proxy Gateway for NanoClawnanocoai/nanoclaw | 31k | — | ~4.6k | Automated safety check: Notes | MIT | |
| GreptimeDB Dev Docker ImageGreptimeTeam/greptimedb | 6.7k | — | ~4k | Automated safety check: Notes | Apache-2.0 | |
| Senior DevOps Toolkitmaslennikov-ig/claude-code-orchestrator-kit | 260 | 6 repos | ~1.1k | Automated safety check: Notes | Custom licence | |
| LangBot Deployment Guidelangbot-app/LangBot | 18k | — | ~1.2k | Automated safety check: Notes | Apache-2.0 | |
| Build Openshell Mxc WindowsNVIDIA/OpenShell | 16k | — | ~4.9k | Automated safety check: Pass | Apache-2.0 |
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More from XLearning-SCU/Active-SWE
Active Swe Eval
XLearning-SCU/Active-SWE
Prepare and run the complete local Docker evaluation for Active-SWE.
Related
Works with
Categories
Questions about Active Swe Eval
What does Active Swe Eval do?
Prepare and orchestrate the complete local Docker evaluation for Active-SWE. Active Swe Eval is an agent skill from XLearning-SCU/Active-SWE. Prepare and orchestrate the complete local Docker evaluation for Active-SWE.
When should I use Active Swe Eval?
Active Swe Eval fits situations like: devOps & Cloud work in your project.
How do I install Active Swe Eval in Claude Code?
Run `npx skills add XLearning-SCU/Active-SWE --skill active-swe-eval -a claude-code`. Or copy the skill folder (.codex/skills/active-swe-eval in XLearning-SCU/Active-SWE) into .claude/skills/active-swe-eval in your project. Claude Code loads it when a task matches its description.
How do I install Active Swe Eval in Codex?
Run `npx skills add XLearning-SCU/Active-SWE --skill active-swe-eval -a codex`. Or copy the skill folder (.codex/skills/active-swe-eval in XLearning-SCU/Active-SWE) into .agents/skills/active-swe-eval in your project. Codex loads it when a task matches its description.
Can I use Active Swe Eval 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 XLearning-SCU/Active-SWE --skill active-swe-eval -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/active-swe-eval, .gemini/skills/active-swe-eval, .github/skills/active-swe-eval and .opencode/skills/active-swe-eval in your project.
What does Active Swe Eval need to run?
Going by SKILL.md and its folder, Active Swe Eval needs the command-line tools its instructions call (git and python). Our summary lists: Python 3; Docker.
Does Active Swe Eval access the network?
SKILL.md names 1 domain. In commands or code: huggingface.co; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Is Active Swe Eval safe to install?
Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Active Swe Eval use?
Active Swe Eval is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Active Swe Eval use?
About 938 tokens (SKILL.md is roughly 3.8k 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 Active Swe Eval?
Skills that share tags, products or a category with Active Swe Eval: Iron Proxy Gateway for NanoClaw (nanocoai/nanoclaw, 31k stars), GreptimeDB Dev Docker Image (GreptimeTeam/greptimedb, 6.7k stars), Senior DevOps Toolkit (maslennikov-ig/claude-code-orchestrator-kit, 260 stars) and LangBot Deployment Guide (langbot-app/LangBot, 18k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Active Swe Eval?
XLearning-SCU (a GitHub user) maintains it in XLearning-SCU/Active-SWE, which has 102 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on August 14, 2026.
Source: XLearning-SCU/Active-SWE on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.