Arize Evaluator
github/awesome-copilot
Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and…
Agent skill
Icra Artifact Evaluation
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when packaging the artifacts behind an ICRA paper — ROS packages, controllers, simulation environments, trained policies, CAD and PCB files, datasets, and trial logs — into…
MITAuto-check passed
Install Icra Artifact Evaluation
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icra-artifact-evaluation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icra-artifact-evaluation --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/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/ICRA-Skills/skills/icra-artifact-evaluation .claude/skills/icra-artifact-evaluation && 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 "icra-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICRA-Skills/skills/icra-artifact-evaluation into .claude/skills/icra-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icra-artifact-evaluation", 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/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICRA-Skills/skills/icra-artifact-evaluationType 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 brycewang-stanford/Awesome-Journal-Skills --skill icra-artifact-evaluation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icra-artifact-evaluation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/ICRA-Skills/skills/icra-artifact-evaluation .agents/skills/icra-artifact-evaluation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "icra-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICRA-Skills/skills/icra-artifact-evaluation into .agents/skills/icra-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icra-artifact-evaluation", 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 brycewang-stanford/Awesome-Journal-Skills --skill icra-artifact-evaluation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icra-artifact-evaluation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/ICRA-Skills/skills/icra-artifact-evaluation .cursor/skills/icra-artifact-evaluation && 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 "icra-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICRA-Skills/skills/icra-artifact-evaluation into .cursor/skills/icra-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icra-artifact-evaluation", 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/brycewang-stanford/Awesome-Journal-Skills.git --path ICRA-Skills/skills/icra-artifact-evaluation--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 brycewang-stanford/Awesome-Journal-Skills --skill icra-artifact-evaluation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icra-artifact-evaluation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/ICRA-Skills/skills/icra-artifact-evaluation .gemini/skills/icra-artifact-evaluation && 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 "icra-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICRA-Skills/skills/icra-artifact-evaluation into .gemini/skills/icra-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icra-artifact-evaluation", 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 brycewang-stanford/Awesome-Journal-Skills icra-artifact-evaluationInstalls 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 brycewang-stanford/Awesome-Journal-Skills --skill icra-artifact-evaluation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/ICRA-Skills/skills/icra-artifact-evaluation .github/skills/icra-artifact-evaluation && 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 "icra-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICRA-Skills/skills/icra-artifact-evaluation into .github/skills/icra-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icra-artifact-evaluation", 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 brycewang-stanford/Awesome-Journal-Skills --skill icra-artifact-evaluation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icra-artifact-evaluation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/ICRA-Skills/skills/icra-artifact-evaluation .opencode/skills/icra-artifact-evaluation && 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 "icra-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICRA-Skills/skills/icra-artifact-evaluation into .opencode/skills/icra-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icra-artifact-evaluation", 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
icra-artifact-evaluation- GitHub stars
- 1.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 702 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when packaging the artifacts behind an ICRA paper — ROS packages, controllers, simulation environments, trained policies, CAD and PCB files, datasets, and trial logs — into…
- Works in 2 steps: Review state: anonymized hosting, no… → Public state (post-acceptance): real…
- Packaging the artifacts behind an ICRA paper — ROS packages
- SKILL.md covers The robotics artifact stack, The five-minute-skeptic standard, Hardware-dependent artifacts and Datasets and logs as artifacts, plus 5 more sections
- Calls docker, git and make
What it does
Icra Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging the artifacts behind an ICRA paper — ROS packages, controllers, simulation environments, trained policies, CAD and PCB files, datasets, and trial logs — into something a robotics reviewer or reader can actually run or audit, given that ICRA has no formal artifact-badging track to certify it for you.
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.
The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的… The licence is MIT.
When your agent uses it
- Packaging the artifacts behind an ICRA paper — ROS packages
- Simulation environments
- Trained policies
- CAD and PCB files
Example prompts
- “/icra-artifact-evaluation”
Requirements
- Python 3
- Docker
Workflow steps
2 steps, taken from the first numbered list in SKILL.md.
- Review state: anonymized hosting, no org/usernames in URLs, git history
- Public state (post-acceptance): real hosting, authors restored, DOI
What it can do on your machine
Read from SKILL.md and the folder at commit 932eb23. 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:
dockergitmake
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use docker and git, 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
Icra Artifact Evaluation loads about 1.6k tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 702 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 brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 702 words, ~1,582 tokens.
Download SKILL.mdSave it as
.claude/skills/icra-artifact-evaluation/SKILL.md (or your agent's skills folder).- name
- icra-artifact-evaluation
- description
- Use when packaging the artifacts behind an ICRA paper — ROS packages, controllers, simulation environments, trained policies, CAD and PCB files, datasets, and trial logs — into something a robotics reviewer or reader can actually run or audit, given that ICRA has no formal artifact-badging track to certify it for you.
ICRA Artifact Evaluation
ICRA, unlike several software-systems conferences, has had no standing artifact evaluation committee or badge system in recent cycles (re-check the current year's calls before asserting this to authors — tracks appear and disappear). The absence cuts both ways: nobody will certify your artifact, and nobody will catch its problems before readers do. This skill applies an artifact-evaluator's discipline voluntarily, because in robotics the artifact often is the contribution's proof.
The robotics artifact stack
A robotics paper's artifact is rarely just "the code." Inventory all six layers and decide, per layer, released / partially released / withheld-with-reason:
| Layer | Typical contents | Common blocker |
|---|---|---|
| Algorithms | planners, controllers, learning code | none — release |
| Integration | ROS launch files, configs, calibration | "works only on our stack" |
| Simulation | worlds, robot models (URDF/SDF), randomization | third-party asset licenses |
| Learned weights | trained policies, perception models | training data licensing |
| Hardware design | CAD, PCB, BOM for custom parts | patent/commercialization plans |
| Evidence | rosbags, trial videos, session sheets | raw-log size (TB-scale) |
A paper whose novelty is a custom end effector but which releases only Python scripts has released the wrong layer. Match the release to the claim.
The five-minute-skeptic standard
Package for a reviewer who gives you five minutes before forming a judgment:
git clone <anonymized-artifact-url> && cd artifact
docker build -t icra-artifact . # or: ./setup.sh — one command, pinned deps
docker run icra-artifact make figure3 # regenerate a headline result in sim
docker run icra-artifact make table2 # recompute stats from released logs
cat CLAIMS.md # claim → command → expected output map- The first runnable thing must not require a robot: a simulation reproduction or a log-replay analysis gives the skeptic a win in minutes.
CLAIMS.mdmaps each paper claim to a command and its expected output, and explicitly lists which claims require physical hardware (audit tier — seeicra-reproducibility).- Pin everything: base image, ROS distro, Python deps, simulator version. "Latest Gazebo" is a bug report generator.
Hardware-dependent artifacts
For layers that need the physical robot:
- Ship a log-replay mode: the perception and decision stack runs against released rosbags, letting readers verify the pipeline without the arm.
- Ship the sim twin: the same launch files targeting the simulated platform, clearly marked as not the source of the paper's hardware numbers.
- Document the hardware interface narrowly (which driver topics/services the stack expects) so ports to other platforms are feasible.
- For custom mechanisms, releasing CAD + BOM converts "trust our gripper" into "build our gripper"; if commercialization blocks this, say so in the paper rather than staying silent.
Datasets and logs as artifacts
- Extracted per-trial features plus a representative raw sample beat an undifferentiated terabyte dump; provide a download script with checksums.
- License explicitly (CC-BY for data, permissive or copyleft choice for code); robotics data with humans in frame needs consent/ethics notes.
- Long-term hosting: university archives, Zenodo-style DOI services, or IEEE DataPort outlive lab NAS boxes and personal cloud links.
Show full SKILL.md (280 more words)Show less
Review-time vs acceptance-time states
Under the double-anonymous policy (2026 cycle onward), the artifact has two lives:
- Review state: anonymized hosting, no org/usernames in URLs, git history squashed (history leaks author emails), license file present but copyright-holder line deferred ("held for anonymity").
- Public state (post-acceptance): real hosting, authors restored, DOI
minted, README linking the IEEE Xplore entry, camera-ready pointing at the
permanent URL (coordinate with
icra-camera-ready).
Prepare both from the start; converting a name-riddled repo to anonymous form in deadline week always misses something.
Safety as an artifact property
Robotics artifacts can move mass. Before anyone external runs your controller:
- Ship conservative default limits (velocity, torque, workspace bounds) and make the paper's aggressive settings an explicit opt-in flag.
- Document the E-stop assumption and any human-proximity constraints in the hardware protocol, not just the lab's tribal knowledge.
- State firmware/driver versions known to behave; a controller tuned on one firmware can oscillate on another, and that failure lands on your artifact's reputation.
Withholding honestly
Legitimate reasons to withhold layers exist (industrial partners, export controls, safety of a hazardous procedure). The rule is disclosure: state in the paper what is withheld and why, and maximize the released remainder — e.g., withheld weights but released training code and evaluation harness. Undisclosed gaps discovered later cost more reputation than declared ones.
Packaging sequence
- Inventory the six layers; mark release state and blockers for each.
- Build the Docker/pinned environment; verify
make figure3on a clean machine. - Write
CLAIMS.md; separate rerunnable from hardware-audit claims. - Add log-replay mode and sim twin for hardware-bound layers.
- Produce the anonymized review state; leak-check URLs, history, metadata.
- Stage the public state for acceptance day.
Output format
[Layer inventory] released: <layers> | partial: <layers> | withheld: <layers+reason>
[Five-minute test] clean-machine run of headline command: pass / fail
[CLAIMS.md] complete: y/n — hardware-only claims flagged: <list>
[Replay/sim twin] present: y/n
[Anonymity state] review-safe: y/n — leaks: <list>
[Hosting] review URL type + acceptance-day plan© brycewang-stanford, 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 ICRA-Skills/skills/icra-artifact-evaluation of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Icra Artifact Evaluation 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 |
|---|---|---|---|---|---|---|
| Icra Artifact Evaluation this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Arize Evaluatorgithub/awesome-copilot | 40k | 1 repos | ~8.1k | Automated safety check: Notes | MIT | |
| Artifacts Buildernexu-io/open-design | 100k | — | ~347 | Automated safety check: Pass | Apache-2.0 | |
| Ccs Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~969 | Automated safety check: Pass | MIT | |
| Mobisys Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1k | Automated safety check: Pass | MIT | |
| Fast Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.6k | Automated safety check: Pass | MIT |
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Questions about Icra Artifact Evaluation
What does Icra Artifact Evaluation do?
A skill your agent uses when packaging the artifacts behind an ICRA paper — ROS packages, controllers, simulation environments, trained policies, CAD and PCB files, datasets, and trial logs — into…. Icra Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging the artifacts behind an ICRA paper — ROS packages, controllers, simulation environments, trained policies, CAD and PCB files, datasets, and trial logs — into something a robotics reviewer or reader can actually run or audit, given that ICRA has no formal artifact-badging track to certify it for you.
When should I use Icra Artifact Evaluation?
Icra Artifact Evaluation fits situations like: packaging the artifacts behind an ICRA paper — ROS packages; simulation environments; trained policies; CAD and PCB files.
How do I install Icra Artifact Evaluation in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icra-artifact-evaluation -a claude-code`. Or copy the skill folder (ICRA-Skills/skills/icra-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/icra-artifact-evaluation in your project. Claude Code loads it when a task matches its description.
How do I install Icra Artifact Evaluation in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icra-artifact-evaluation -a codex`. Or copy the skill folder (ICRA-Skills/skills/icra-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/icra-artifact-evaluation in your project. Codex loads it when a task matches its description.
Can I use Icra Artifact Evaluation 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 brycewang-stanford/Awesome-Journal-Skills --skill icra-artifact-evaluation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/icra-artifact-evaluation, .gemini/skills/icra-artifact-evaluation, .github/skills/icra-artifact-evaluation and .opencode/skills/icra-artifact-evaluation in your project.
What does Icra Artifact Evaluation need to run?
Going by SKILL.md and its folder, Icra Artifact Evaluation needs the command-line tools its instructions call (docker, git and make). Our summary lists: Python 3; Docker.
Does Icra Artifact Evaluation access the network?
SKILL.md contains no URLs. Its commands use docker and git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Icra Artifact Evaluation 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 Icra Artifact Evaluation use?
Icra Artifact Evaluation 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 Icra Artifact Evaluation use?
About 1.6k tokens (SKILL.md is roughly 6.3k 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 Icra Artifact Evaluation?
Skills that share tags, products or a category with Icra Artifact Evaluation: Arize Evaluator (github/awesome-copilot, 40k stars), Artifacts Builder (nexu-io/open-design, 100k stars), Ccs Artifact Evaluation (brycewang-stanford/Awesome-Journal-Skills, 1.2k stars) and Mobisys Artifact Evaluation (brycewang-stanford/Awesome-Journal-Skills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Icra Artifact Evaluation?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,231 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.
Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.