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.
Benchmark chunkah packing algorithm changes against a series of OCI images.
Install Benchmark Packing
$ npx skills add coreos/chunkah --skill benchmark-packing -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install coreos/chunkah benchmark-packing --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/coreos/chunkah.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/benchmark-packing .claude/skills/benchmark-packing && 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 "benchmark-packing" agent skill from https://github.com/coreos/chunkah/tree/main/.agents/skills/benchmark-packing into .claude/skills/benchmark-packing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchmark-packing", 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/coreos/chunkah/tree/main/.agents/skills/benchmark-packingType 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 coreos/chunkah --skill benchmark-packing -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install coreos/chunkah benchmark-packing --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/coreos/chunkah.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/benchmark-packing .agents/skills/benchmark-packing && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "benchmark-packing" agent skill from https://github.com/coreos/chunkah/tree/main/.agents/skills/benchmark-packing into .agents/skills/benchmark-packing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchmark-packing", 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 coreos/chunkah --skill benchmark-packing -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install coreos/chunkah benchmark-packing --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/coreos/chunkah.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/benchmark-packing .cursor/skills/benchmark-packing && 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 "benchmark-packing" agent skill from https://github.com/coreos/chunkah/tree/main/.agents/skills/benchmark-packing into .cursor/skills/benchmark-packing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchmark-packing", 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/coreos/chunkah.git --path .agents/skills/benchmark-packing--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 coreos/chunkah --skill benchmark-packing -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install coreos/chunkah benchmark-packing --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/coreos/chunkah.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/benchmark-packing .gemini/skills/benchmark-packing && 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 "benchmark-packing" agent skill from https://github.com/coreos/chunkah/tree/main/.agents/skills/benchmark-packing into .gemini/skills/benchmark-packing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchmark-packing", 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 coreos/chunkah benchmark-packingInstalls 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 coreos/chunkah --skill benchmark-packing -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/coreos/chunkah.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/benchmark-packing .github/skills/benchmark-packing && 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 "benchmark-packing" agent skill from https://github.com/coreos/chunkah/tree/main/.agents/skills/benchmark-packing into .github/skills/benchmark-packing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchmark-packing", 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 coreos/chunkah --skill benchmark-packing -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install coreos/chunkah benchmark-packing --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/coreos/chunkah.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/benchmark-packing .opencode/skills/benchmark-packing && 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 "benchmark-packing" agent skill from https://github.com/coreos/chunkah/tree/main/.agents/skills/benchmark-packing into .opencode/skills/benchmark-packing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "benchmark-packing", 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
benchmark-packing- GitHub stars
- 148
- Token cost
- ~1.1k tokens
- SKILL.md length
- 388 words
- Files
- 1
- Skills in repo
- 4
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Benchmark chunkah packing algorithm changes against a series of OCI images.
- Works in 6 steps: Build chunkah → Prepare source images → Chunk the series → …
- Tasks that involve Containers
- SKILL.md covers Overview, Pipeline, Comparing multiple… and Pitfalls
- Calls podman and just
What it does
Benchmark Packing is an agent skill from coreos/chunkah. Benchmark chunkah packing algorithm changes against a series of OCI images.
Its SKILL.md is about 1.1k 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 DevOps & Cloud, covering Containers. The repository describes itself as: An OCI building tool for content-based layers. The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Containers
Example prompts
- “/benchmark-packing”
Requirements
- Docker
Workflow steps
6 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 780bcd2. 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:
podmanjust
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
Benchmark Packing loads about 1.1k tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 388 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); files beside SKILL.md are not scanned.
SKILL.md
The full file from coreos/chunkah at commit 780bcd2, republished under its Apache-2.0 licence (© coreos). 388 words, ~1,050 tokens.
Download SKILL.mdSave it as
.claude/skills/benchmark-packing/SKILL.md (or your agent's skills folder).- name
- benchmark-packing
- description
- Benchmark chunkah packing algorithm changes against a series of OCI images.
Benchmark Packing
Overview
This skill guides benchmarking of packing algorithm changes by chunking a series of consecutive OCI images and measuring layer reuse between them. The key tools are:
tools/chunk-image-series.py-- chunks a series of imagestools/analyze-layer-reuse.py-- compares layer sharing across the chunked series
Pipeline
1. Build chunkah
After making code changes, build the container image:
just buildimg --no-chunkThis produces localhost/chunkah:latest.
2. Prepare source images
Source images must be in containers-storage. Either:
From OCI archives:
for archive in /path/to/*.ociarchive; do
version=$(echo "${archive}" | grep -oP 'PATTERN')
skopeo copy "oci-archive:${archive}" "containers-storage:localhost/myrepo:${version}"
doneFrom a registry:
chunk-image-series.py can pull directly from a registry:
tools/chunk-image-series.py docker://quay.io/fedora/fedora-coreos \
--tag-filter '43.*' --limit 10 ...3. Chunk the series
tools/chunk-image-series.py containers-storage:localhost/myrepo \
--tag-filter '43.*' \
--prefix myrepo-chunked \
--chunkah-image localhost/chunkah \
--force \
-- --prune /sysroot --max-layers 128Key flags:
--forceto overwrite results from prior runs--limit Nto control how many images to process- Extra chunkah args go after
--
4. Analyze layer reuse
Pass all chunked images as separate positional arguments:
image_args=()
for i in $(seq 0 9); do
image_args+=("containers-storage:localhost/myrepo-chunked:${i}")
done
tools/analyze-layer-reuse.py --json "${image_args[@]}" > results.jsonIMPORTANT: do NOT use brace expansion inside quotes (e.g.
"...:{0,1,2}") -- it won't expand. Always build the argument
list explicitly.
The JSON summary fields are:
avg_reuse_ratio-- fraction of data shared (0.0 to 1.0)avg_download_bytes-- average new data per update
5. Clean up chunked images
Always clean up chunked images after capturing results:
for i in $(seq 0 9); do
podman rmi "localhost/myrepo-chunked:${i}" 2>/dev/null || true
done6. Compare against original packing
Always measure the original (un-chunked) images as a baseline:
image_args=()
for tag in $(podman images --filter reference='localhost/myrepo' \
--format '{{.Tag}}' | sort); do
image_args+=("containers-storage:localhost/myrepo:${tag}")
done
tools/analyze-layer-reuse.py --json "${image_args[@]}" > original.jsonComparing multiple configurations
To compare a code change against the current defaults:
- Chunk with the baseline chunkah (
quay.io/coreos/chunkah:dev) - Capture and save JSON results
- Clean up chunked images
- Build local chunkah with your changes
- Chunk with
localhost/chunkah - Capture and save JSON results
- Clean up chunked images
- Compare the two JSON files
The source images and original baseline can be reused across runs.
Show full SKILL.md (133 more words)Show less
Pitfalls
Duplicate tags
chunk-image-series.py creates temporary localhost/tmp-chunk-src
tags during chunking. These are cleaned up on exit, but if a prior
run was interrupted, stale tags may remain and cause duplicate
entries. Before running analysis, verify tags are clean:
podman images --filter reference='localhost/myrepo' --format '{{.Tag}}' | sortIf you see duplicate tags, remove them before proceeding. A red
flag in results is min_download_bytes: 0 -- this means two
consecutive images were identical (likely duplicates).
Sample size sensitivity
Results can vary significantly depending on the specific time window of builds tested. Always test against multiple independent corpora (e.g. different image types, different time periods) before concluding a change is beneficial. An improvement on one sample may not generalize.
Layer count matters
The default --max-layers is 64. Results at 64 layers vs 128
layers can differ substantially. Always compare configurations at
the same layer count.
© coreos, 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
Just SKILL.md in .agents/skills/benchmark-packing of coreos/chunkah.
Open the folder on GitHubat commit 780bcd2
Compare with similar skills
Benchmark Packing 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 |
|---|---|---|---|---|---|---|
| Benchmark Packing this skillcoreos/chunkah | 148 | — | ~1.1k | Automated safety check: Pass | 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 | 259 | 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 | 15k | — | ~4.9k | Automated safety check: Pass | Apache-2.0 |
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GreptimeDB Dev Docker Image
GreptimeTeam/greptimedb
Packages a locally built GreptimeDB debug binary into a development-only Docker image for local-cluster testing, with an optional push to a dev registry.
Senior DevOps Toolkit
maslennikov-ig/claude-code-orchestrator-kit
Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup…
LangBot Deployment Guide
langbot-app/LangBot
Deploys and configures a LangBot instance with Docker Compose or Kubernetes, covering config.yaml, the Box sandbox runtime, the plugin runtime and the global API key.
- Official
Build Openshell Mxc Windows
NVIDIA/OpenShell
Maintain and validate OpenShell's build-only Windows MSVC lane for x64 and ARM64.
Omnigent Docker Compose Deploy
omnigent-ai/omnigent
Brings up the Omnigent server and Postgres as a Docker compose stack on any Docker host, and covers the Dockerfile's runtime and host build targets for extending it to a new platform.
More from coreos/chunkah
Alloc Tracker
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Related
Categories
Questions about Benchmark Packing
What does Benchmark Packing do?
Benchmark chunkah packing algorithm changes against a series of OCI images. Benchmark Packing is an agent skill from coreos/chunkah. Benchmark chunkah packing algorithm changes against a series of OCI images.
When should I use Benchmark Packing?
Benchmark Packing fits situations like: tasks that involve Containers.
How do I install Benchmark Packing in Claude Code?
Run `npx skills add coreos/chunkah --skill benchmark-packing -a claude-code`. Or copy the skill folder (.agents/skills/benchmark-packing in coreos/chunkah) into .claude/skills/benchmark-packing in your project. Claude Code loads it when a task matches its description.
How do I install Benchmark Packing in Codex?
Run `npx skills add coreos/chunkah --skill benchmark-packing -a codex`. Or copy the skill folder (.agents/skills/benchmark-packing in coreos/chunkah) into .agents/skills/benchmark-packing in your project. Codex loads it when a task matches its description.
Can I use Benchmark Packing 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 coreos/chunkah --skill benchmark-packing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/benchmark-packing, .gemini/skills/benchmark-packing, .github/skills/benchmark-packing and .opencode/skills/benchmark-packing in your project.
What does Benchmark Packing need to run?
Going by SKILL.md and its folder, Benchmark Packing needs the command-line tools its instructions call (podman and just). Our summary lists: Docker.
Does Benchmark Packing 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 Benchmark Packing 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 Benchmark Packing use?
Benchmark Packing 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 Benchmark Packing use?
About 1.1k tokens (SKILL.md is roughly 4.2k 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 Benchmark Packing?
Skills that share tags, products or a category with Benchmark Packing: 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, 259 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 Benchmark Packing?
coreos (a GitHub organization) maintains it in coreos/chunkah, which has 148 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on October 5, 2026.
Source: coreos/chunkah on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.