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
Ipsn Artifact Evaluation
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when packaging an IPSN-lineage artifact for the ACM badges and the IPSN Best Research Artifact Award, covering hardware-plus-software artifacts (firmware, board files…
MITAuto-check passed
Install Ipsn Artifact Evaluation
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ipsn-artifact-evaluation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ipsn-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/IPSN-Skills/skills/ipsn-artifact-evaluation .claude/skills/ipsn-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 "ipsn-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IPSN-Skills/skills/ipsn-artifact-evaluation into .claude/skills/ipsn-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ipsn-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/IPSN-Skills/skills/ipsn-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 ipsn-artifact-evaluation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ipsn-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/IPSN-Skills/skills/ipsn-artifact-evaluation .agents/skills/ipsn-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 "ipsn-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IPSN-Skills/skills/ipsn-artifact-evaluation into .agents/skills/ipsn-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ipsn-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 ipsn-artifact-evaluation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ipsn-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/IPSN-Skills/skills/ipsn-artifact-evaluation .cursor/skills/ipsn-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 "ipsn-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IPSN-Skills/skills/ipsn-artifact-evaluation into .cursor/skills/ipsn-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ipsn-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 IPSN-Skills/skills/ipsn-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 ipsn-artifact-evaluation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ipsn-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/IPSN-Skills/skills/ipsn-artifact-evaluation .gemini/skills/ipsn-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 "ipsn-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IPSN-Skills/skills/ipsn-artifact-evaluation into .gemini/skills/ipsn-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ipsn-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 ipsn-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 ipsn-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/IPSN-Skills/skills/ipsn-artifact-evaluation .github/skills/ipsn-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 "ipsn-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IPSN-Skills/skills/ipsn-artifact-evaluation into .github/skills/ipsn-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ipsn-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 ipsn-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 ipsn-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/IPSN-Skills/skills/ipsn-artifact-evaluation .opencode/skills/ipsn-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 "ipsn-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IPSN-Skills/skills/ipsn-artifact-evaluation into .opencode/skills/ipsn-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ipsn-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
ipsn-artifact-evaluation- GitHub stars
- 1.2k
- Token cost
- ~1.5k tokens
- SKILL.md length
- 623 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when packaging an IPSN-lineage artifact for the ACM badges and the IPSN Best Research Artifact Award, covering hardware-plus-software artifacts (firmware, board files…
- Packaging an IPSN-lineage artifact for the ACM badges and the IPSN Best Research Artifact Award
- SKILL.md covers Badges and the award (verify…, What sensor-systems evaluators…, Packaging plan and Anonymized review artifact vs.…, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Covering hardware-plus-software artifacts (firmware
What it does
Ipsn Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging an IPSN-lineage artifact for the ACM badges and the IPSN Best Research Artifact Award, covering hardware-plus-software artifacts (firmware, board files, datasets), what sensor-systems evaluators check first, DOI-issuing archives, evaluator-proof documentation for a physical system, and the separate post-acceptance timing.
Its SKILL.md is about 1.5k 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 an IPSN-lineage artifact for the ACM badges and the IPSN Best Research Artifact Award
- Covering hardware-plus-software artifacts (firmware
- What sensor-systems evaluators check first
- DOI-issuing archives
Example prompts
- “/ipsn-artifact-evaluation”
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
No scripts in the folder and no shell commands in SKILL.md.
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
Ipsn Artifact Evaluation loads about 1.5k tokens when it runs. Until then it costs about 92 tokens; SKILL.md has 623 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). 623 words, ~1,536 tokens.
Download SKILL.mdSave it as
.claude/skills/ipsn-artifact-evaluation/SKILL.md (or your agent's skills folder).- name
- ipsn-artifact-evaluation
- description
- Use when packaging an IPSN-lineage artifact for the ACM badges and the IPSN Best Research Artifact Award, covering hardware-plus-software artifacts (firmware, board files, datasets), what sensor-systems evaluators check first, DOI-issuing archives, evaluator-proof documentation for a physical system, and the separate post-acceptance timing.
IPSN Artifact Evaluation
Use this for the artifact track. IPSN had a strong artifact culture — a Best Research Artifact Award alongside the Best Paper Award — and its artifacts are unusual because they mix hardware, firmware, and data, not just code. Two things to internalize: badges and the award are earned by evaluators actually using your package, and the review artifact (anonymized, for the paper's reviewers) is not the same deliverable as the public artifact (de-anonymized, DOI-archived). Because IPSN merged into SenSys, confirm the current badge set, the award's persistence, and the deadline on the successor call (待核实).
Badges and the award (verify the current set)
| Target | What it certifies | What earns it |
|---|---|---|
| Artifacts Available (ACM) | The artifact is permanently, publicly retrievable | Deposit in a DOI-issuing archive (Zenodo, IEEE DataPort, figshare, Software Heritage) |
| Artifacts Evaluated - Functional | The artifact runs and does what the paper says | A clean-machine (or emulated) install, a demo, documented expected outputs |
| Artifacts Evaluated - Reusable | Others can build on it | The Functional bar plus careful docs, structure, licensing, and board/firmware detail |
| Results Reproduced | An evaluator reproduced key results | A turnkey analysis path from raw traces to the headline numbers |
| IPSN Best Research Artifact Award | Community recognition of an exceptional artifact | A package an evaluator can genuinely run and reuse, hardware caveats stated honestly |
Available is low-cost, high-value (archive the package). Functional/Reusable/Reproduced require the evaluator's own run to succeed — and for sensor systems, the failure mode is usually "needs hardware we don't have," so a software/analysis path that reproduces from logged traces is what keeps the artifact usable when the board is not on the evaluator's bench.
What sensor-systems evaluators open first
| Claim type | First thing inspected | Common failure caught |
|---|---|---|
| An estimator / IP method | The scripts that turn raw traces into the paper's figures | Numbers in the PDF that no script reproduces |
| A platform / SPOTS tool | The firmware build + a run on real or emulated hardware | Undocumented toolchain; only-builds-on-authors'-bench |
| A dataset | The raw traces + the extraction/processing scripts + ground truth | Data shipped without the ground truth or the processing |
| An on-device model | Firmware + quantized model + a way to run inference | Requires the exact board and undocumented setup |
| A deployment | Raw traces + analysis, with a clear "needs the site" statement | In-field numbers no evaluator can approach |
Assume an evaluator gives your package a bounded time budget and may not have your hardware. Design the analysis path to succeed on any machine; design the hardware path to be honest about what it needs.
Show full SKILL.md (212 more words)Show less
Packaging plan
[Analysis path] a turnkey script set that regenerates each figure from logged raw traces, on any machine
[Firmware] sources + build instructions + pinned toolchain (compiler/SDK/RTOS) + board revision
[Hardware] BOM / board files, and a clear "you will need X" statement where the board is required
[Data] raw traces + the ground-truth reference (with its error) + calibration data
[Mapping] an explicit table: paper claim -> script/firmware -> expected result
[Harness] the energy/latency measurement setup and conditions, so numbers can be re-measured
[License] an OSI-approved license for code, an open data license for datasets
[Archive] DOI-issuing repository for the Available badge (Zenodo / IEEE DataPort / figshare)Anonymized review artifact vs. public artifact
- At submission: anonymized for the paper's reviewers — no owner strings, lab-named testbeds, board silkscreen logos, or identity-revealing dataset DOIs; scrub scope-screenshot watermarks.
- After acceptance: replace anonymized placeholders with the public, licensed, DOI-issuing archive; this is the version evaluators badge, the award judges assess, and the camera-ready cites.
Worked vignette: packaging an on-device sensing artifact
A paper contributes a TinyML detector and a deployment. To target Reusable, Reproduced, and the
award: ship firmware sources with a pinned toolchain and board revision; a reproduce/ directory
whose scripts regenerate every figure from the bundled raw traces on any laptop; the quantized model
and a way to run inference (on the board or an emulator); the labeled field traces with ground-truth
error stated; the power-measurement harness and conditions; an MIT/Apache code license and an open
data license; and a DOI archive. State honestly which results are turnkey (analysis from traces) and
which need the physical board or the deployment site.
Calibration
- The artifact process is typically post-acceptance with its own deadline; do not conflate it with the camera-ready. Confirm the successor's timing and whether the Best Research Artifact Award persists (待核实).
- Badge names, the exact set, and whether evaluation is single- or double-anonymous vary by cycle.
Output format
[Target] Available / Functional / Reusable / Reproduced / Best Research Artifact Award
[Artifact role] anonymized review artifact / public DOI-archived artifact
[Contents] <firmware / BOM / traces / ground truth / harness / license>
[Analysis path] does figure regeneration from logged traces succeed on any machine? yes/no
[Hardware honesty] is "you will need X hardware" stated clearly? yes/no
[Claim mapping] <claim -> script/firmware -> expected result present? yes/no>
[Fixes before upload] <ordered list>© 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 IPSN-Skills/skills/ipsn-artifact-evaluation of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Ipsn 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 |
|---|---|---|---|---|---|---|
| Ipsn Artifact Evaluation this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.5k | Automated safety check: Pass | MIT | |
| Arize Evaluatorgithub/awesome-copilot | 40k | 1 repos | ~8.1k | Automated safety check: Notes | MIT | |
| Ccs Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~969 | Automated safety check: Pass | MIT | |
| Sigcomm Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Sigmetrics Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.4k | Automated safety check: Pass | MIT | |
| Socc Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.5k | Automated safety check: Pass | MIT |
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Questions about Ipsn Artifact Evaluation
What does Ipsn Artifact Evaluation do?
A skill your agent uses when packaging an IPSN-lineage artifact for the ACM badges and the IPSN Best Research Artifact Award, covering hardware-plus-software artifacts (firmware, board files…. Ipsn Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging an IPSN-lineage artifact for the ACM badges and the IPSN Best Research Artifact Award, covering hardware-plus-software artifacts (firmware, board files, datasets), what sensor-systems evaluators check first, DOI-issuing archives, evaluator-proof documentation for a physical system, and the separate post-acceptance timing.
When should I use Ipsn Artifact Evaluation?
Ipsn Artifact Evaluation fits situations like: packaging an IPSN-lineage artifact for the ACM badges and the IPSN Best Research Artifact Award; covering hardware-plus-software artifacts (firmware; what sensor-systems evaluators check first; DOI-issuing archives.
How do I install Ipsn Artifact Evaluation in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ipsn-artifact-evaluation -a claude-code`. Or copy the skill folder (IPSN-Skills/skills/ipsn-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/ipsn-artifact-evaluation in your project. Claude Code loads it when a task matches its description.
How do I install Ipsn Artifact Evaluation in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ipsn-artifact-evaluation -a codex`. Or copy the skill folder (IPSN-Skills/skills/ipsn-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/ipsn-artifact-evaluation in your project. Codex loads it when a task matches its description.
Can I use Ipsn 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 ipsn-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/ipsn-artifact-evaluation, .gemini/skills/ipsn-artifact-evaluation, .github/skills/ipsn-artifact-evaluation and .opencode/skills/ipsn-artifact-evaluation in your project.
What does Ipsn Artifact Evaluation need to run?
SKILL.md names no scripts, command-line tools or credentials: Ipsn Artifact Evaluation is instructions for the agent only.
Does Ipsn Artifact Evaluation 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 Ipsn 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 Ipsn Artifact Evaluation use?
Ipsn 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 Ipsn Artifact Evaluation use?
About 1.5k tokens (SKILL.md is roughly 6.1k 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 Ipsn Artifact Evaluation?
Skills that share tags, products or a category with Ipsn Artifact Evaluation: Arize Evaluator (github/awesome-copilot, 40k stars), Ccs Artifact Evaluation (brycewang-stanford/Awesome-Journal-Skills, 1.2k stars), Sigcomm Artifact Evaluation (brycewang-stanford/Awesome-Journal-Skills, 1.2k stars) and Sigmetrics 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 Ipsn 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.