Jqte Io Cge
franklee16/academic-research-skills
A skill your agent uses when a 《数量经济技术经济研究》 (JQTE) manuscript is built on an input-output table, a CGE model, or a structural decomposition (SDA).
A skill your agent uses when strengthening IPSN-lineage reproducibility for a hardware/embedded/deployment artifact, covering firmware and board files, pinned toolchains, raw traces and calibration…
Install Ipsn Reproducibility
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ipsn-reproducibility -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ipsn-reproducibility --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-reproducibility .claude/skills/ipsn-reproducibility && 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-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IPSN-Skills/skills/ipsn-reproducibility into .claude/skills/ipsn-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ipsn-reproducibility", 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-reproducibilityType 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-reproducibility -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ipsn-reproducibility --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-reproducibility .agents/skills/ipsn-reproducibility && 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-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IPSN-Skills/skills/ipsn-reproducibility into .agents/skills/ipsn-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ipsn-reproducibility", 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-reproducibility -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ipsn-reproducibility --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-reproducibility .cursor/skills/ipsn-reproducibility && 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-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IPSN-Skills/skills/ipsn-reproducibility into .cursor/skills/ipsn-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ipsn-reproducibility", 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-reproducibility--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-reproducibility -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ipsn-reproducibility --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-reproducibility .gemini/skills/ipsn-reproducibility && 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-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IPSN-Skills/skills/ipsn-reproducibility into .gemini/skills/ipsn-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ipsn-reproducibility", 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-reproducibilityInstalls 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-reproducibility -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-reproducibility .github/skills/ipsn-reproducibility && 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-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IPSN-Skills/skills/ipsn-reproducibility into .github/skills/ipsn-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ipsn-reproducibility", 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-reproducibility -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-reproducibility --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-reproducibility .opencode/skills/ipsn-reproducibility && 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-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IPSN-Skills/skills/ipsn-reproducibility into .opencode/skills/ipsn-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ipsn-reproducibility", 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-reproducibility- GitHub stars
- 1.2k
- Token cost
- ~1.4k tokens
- SKILL.md length
- 585 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when strengthening IPSN-lineage reproducibility for a hardware/embedded/deployment artifact, covering firmware and board files, pinned toolchains, raw traces and calibration…
- Strengthening IPSN-lineage reproducibility for a hardware/embedded/deployment artifact
- SKILL.md covers Evidence map, What a sensor-systems artifact…, Provenance pinning and Degrees of reproducibility…, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Covering firmware and board files
What it does
Ipsn Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when strengthening IPSN-lineage reproducibility for a hardware/embedded/deployment artifact, covering firmware and board files, pinned toolchains, raw traces and calibration, honest degrees of reproducibility for a physical system, anonymized-but-runnable artifacts, and consistency between the paper and the package.
Its SKILL.md is about 1.4k 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 Research & Science, covering Reproducible research and Performance reviews. 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
- Strengthening IPSN-lineage reproducibility for a hardware/embedded/deployment artifact
- Covering firmware and board files
- Pinned toolchains
- Raw traces and calibration
Example prompts
- “/ipsn-reproducibility”
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 Reproducibility loads about 1.4k tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 585 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). 585 words, ~1,423 tokens.
Download SKILL.mdSave it as
.claude/skills/ipsn-reproducibility/SKILL.md (or your agent's skills folder).- name
- ipsn-reproducibility
- description
- Use when strengthening IPSN-lineage reproducibility for a hardware/embedded/deployment artifact, covering firmware and board files, pinned toolchains, raw traces and calibration, honest degrees of reproducibility for a physical system, anonymized-but-runnable artifacts, and consistency between the paper and the package.
IPSN Reproducibility
Use this before submission and again before camera-ready. IPSN's artifact and Best Research Artifact culture makes reproducibility a scored dimension — but a sensor-systems artifact is harder than a software one: it involves firmware, hardware, physical ground truth, and measurements that depend on the bench. The goal is that a competent reader could rebuild as much of your evidence as the physical setup allows, and knows exactly which parts need your hardware.
Evidence map
- Map each claim and reported number to a verifiable location — a paper section, a figure generated from logged traces, a firmware build, or a script in the artifact.
- For an IP-track method, give the algorithm, parameters, and the analysis scripts that turn raw traces into the paper's figures.
- For a SPOTS-track platform, ship firmware sources, build instructions, a bill of materials or board files, and the pinned toolchain (compiler, SDK, RTOS versions).
- For a deployment, ship the raw sensor traces, the ground-truth reference, and the calibration data — not only the derived metrics.
- Keep the paper and artifact consistent: a number in the PDF that no script or trace in the artifact produces is the contradiction reviewers read as carelessness.
What a sensor-systems artifact contains
| Component | Weak version | IPSN-ready version |
|---|---|---|
| Firmware | "Available on request" | Sources + build instructions + pinned toolchain, flashable or emulatable |
| Hardware | "We built a custom board" | BOM / board files, or a clear statement of what needs the physical board |
| Datasets | "Dataset available on request" | Anonymized raw traces + the exact processing scripts, DOI-archived after acceptance |
| Ground truth | Nothing | Surveyed positions / labels / reference-instrument data with its own error |
| Energy/latency | "Measured on our setup" | The measurement harness + conditions (rail, instrument, clock, runs) |
| Calibration | Implicit | Procedure, date, and drift data |
"Available on request" is treated as not available; convert every such line into a concrete, anonymized package or an explicit, justified exception (e.g., proprietary board, private deployment site).
Provenance pinning
[Firmware] pin compiler/SDK/RTOS versions; record board revision; make the build deterministic
[Traces] archive raw sensor data with timestamps; record the sensor and sampling regime
[Ground truth] archive the reference data and state its measurement error
[Energy] record the measurement harness (rail, shunt, instrument, sampling rate) and the platform clock
[Learned parts] record model versions, quantization, seeds; cache inputs/outputs for any offline stepShow full SKILL.md (273 more words)Show less
Degrees of reproducibility (state the one you achieved)
- Turnkey (software path): one documented command regenerates each figure from logged traces.
- Hardware-in-the-loop: reproducing requires the board/sensor; you provide firmware, BOM, and a clear "you will need X hardware" statement.
- Deployment-bound: the in-field result cannot be re-run without the site; you provide the raw traces and analysis so the processing reproduces even if the collection cannot.
For IPSN, aim turnkey for the analysis path (traces → figures) and be explicit about the hardware/deployment parts that cannot be reproduced without your equipment. Stating the achieved level honestly beats promising turnkey behavior that fails on an evaluator's bench.
Anonymized but runnable (double-blind)
- No author/lab strings in firmware repos, board silkscreen, dataset DOIs, or file paths.
- Board photos and scope screenshots stripped of lab logos and watermarks; testbed/site names generalized.
- The artifact opens clean: no
.githistory, credentials, or lab-identifying README.
Consistency and camera-ready pass
- Before submission: every scored number traces to the artifact; the release statement matches reality; the package is anonymized.
- Before camera-ready: swap anonymized links for permanent, DOI-issuing archives (Zenodo / IEEE
DataPort / figshare), restore real names, and align with the badges and Best Research Artifact
Award you are pursuing (
ipsn-artifact-evaluation).
Vignette: a deployment plus estimator
A paper deploys nodes and proposes an estimator. Its reproducibility spine: firmware sources with a pinned toolchain and board revision; the raw traces and the surveyed ground truth; the calibration procedure and drift log; the analysis scripts that turn traces into every figure; the power-measurement harness and conditions; and one honest paragraph on what needs the physical board and the deployment site and therefore cannot be re-collected — only re-processed.
Output format
[Claim inventory] <claim -> evidence location (section / figure / firmware / trace / script)>
[Artifact completeness] firmware / BOM / traces / ground truth / calibration / harness present?
[Reproducibility level] turnkey / hardware-in-the-loop / deployment-bound, stated honestly
[Provenance gaps] <toolchain pins / trace archive / energy conditions / seeds>
[Anonymity] package + hardware imagery clean of identity? passed/issues
[Fixes] <paper fixes that must appear + artifact additions before upload>© 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-reproducibility of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Ipsn Reproducibility 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 Reproducibility this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.4k | Automated safety check: Pass | MIT | |
| Jqte Io Cgefranklee16/academic-research-skills | 223 | 1 repos | ~419 | Automated safety check: Pass | None | |
| Peer ReviewK-Dense-AI/claude-scientific-writer | 2.4k | 2 repos | ~3.1k | Automated safety check: Notes | MIT | |
| CHARLS Paper Reproduction Guidexjtulyc/MedgeClaw | 617 | 1 repos | ~1.8k | Automated safety check: Pass | None | |
| Compute Environment Setupaipoch/open-science | 5.5k | — | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Figure Styleaipoch/open-science | 5.5k | — | ~5.1k | Automated safety check: Pass | Apache-2.0 |
Similar skills
Peer Review
K-Dense-AI/claude-scientific-writer
Prepare evidence-bounded, constructive peer-review drafts and structured manuscript assessments.
CHARLS Paper Reproduction Guide
xjtulyc/MedgeClaw
Guides an agent through reproducing papers built on the CHARLS health and retirement survey, from variable mapping to cognition, depression and isolation scores.
Compute Environment Setup
aipoch/open-science
Prepares setup instructions and a named activation file for a user-managed software environment on an Open-Science SSH or Slurm compute host.
Figure Style
aipoch/open-science
Publication-grade correctness and legibility rules for final-deliverable scientific figures, not exploratory plots.
Add Bactopia Tool
bactopia/bactopia
Scaffold a complete Bactopia Tool across all three tiers -- module, subworkflow, and workflow entry point under workflows/bactopia-tools/.
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Categories
Questions about Ipsn Reproducibility
What does Ipsn Reproducibility do?
A skill your agent uses when strengthening IPSN-lineage reproducibility for a hardware/embedded/deployment artifact, covering firmware and board files, pinned toolchains, raw traces and calibration…. Ipsn Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when strengthening IPSN-lineage reproducibility for a hardware/embedded/deployment artifact, covering firmware and board files, pinned toolchains, raw traces and calibration, honest degrees of reproducibility for a physical system, anonymized-but-runnable artifacts, and consistency between the paper and the package.
When should I use Ipsn Reproducibility?
Ipsn Reproducibility fits situations like: strengthening IPSN-lineage reproducibility for a hardware/embedded/deployment artifact; covering firmware and board files; pinned toolchains; raw traces and calibration.
How do I install Ipsn Reproducibility in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ipsn-reproducibility -a claude-code`. Or copy the skill folder (IPSN-Skills/skills/ipsn-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/ipsn-reproducibility in your project. Claude Code loads it when a task matches its description.
How do I install Ipsn Reproducibility in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ipsn-reproducibility -a codex`. Or copy the skill folder (IPSN-Skills/skills/ipsn-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/ipsn-reproducibility in your project. Codex loads it when a task matches its description.
Can I use Ipsn Reproducibility 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-reproducibility -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-reproducibility, .gemini/skills/ipsn-reproducibility, .github/skills/ipsn-reproducibility and .opencode/skills/ipsn-reproducibility in your project.
What does Ipsn Reproducibility need to run?
SKILL.md names no scripts, command-line tools or credentials: Ipsn Reproducibility is instructions for the agent only.
Does Ipsn Reproducibility 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 Reproducibility 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 Reproducibility use?
Ipsn Reproducibility 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 Reproducibility use?
About 1.4k tokens (SKILL.md is roughly 5.7k 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 Reproducibility?
Skills that share tags, products or a category with Ipsn Reproducibility: Jqte Io Cge (franklee16/academic-research-skills, 223 stars), Peer Review (K-Dense-AI/claude-scientific-writer, 2.4k stars), CHARLS Paper Reproduction Guide (xjtulyc/MedgeClaw, 617 stars) and Compute Environment Setup (aipoch/open-science, 5.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Ipsn Reproducibility?
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.