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 hardening an ICRA paper's reproducibility — specifying robot platform, firmware, ROS and driver versions, control rates, and sensor calibration; logging rosbags and…
Install Icra Reproducibility
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icra-reproducibility -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icra-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/ICRA-Skills/skills/icra-reproducibility .claude/skills/icra-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 "icra-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICRA-Skills/skills/icra-reproducibility into .claude/skills/icra-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icra-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/ICRA-Skills/skills/icra-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 icra-reproducibility -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icra-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/ICRA-Skills/skills/icra-reproducibility .agents/skills/icra-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 "icra-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICRA-Skills/skills/icra-reproducibility into .agents/skills/icra-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icra-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 icra-reproducibility -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icra-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/ICRA-Skills/skills/icra-reproducibility .cursor/skills/icra-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 "icra-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICRA-Skills/skills/icra-reproducibility into .cursor/skills/icra-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icra-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 ICRA-Skills/skills/icra-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 icra-reproducibility -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icra-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/ICRA-Skills/skills/icra-reproducibility .gemini/skills/icra-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 "icra-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICRA-Skills/skills/icra-reproducibility into .gemini/skills/icra-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icra-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 icra-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 icra-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/ICRA-Skills/skills/icra-reproducibility .github/skills/icra-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 "icra-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICRA-Skills/skills/icra-reproducibility into .github/skills/icra-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icra-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 icra-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 icra-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/ICRA-Skills/skills/icra-reproducibility .opencode/skills/icra-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 "icra-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICRA-Skills/skills/icra-reproducibility into .opencode/skills/icra-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icra-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
icra-reproducibility- GitHub stars
- 1.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 662 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when hardening an ICRA paper's reproducibility — specifying robot platform, firmware, ROS and driver versions, control rates, and sensor calibration; logging rosbags and…
- Works in 6 steps: Specification ledger complete in-paper… → Every reported number regenerates from… → Seeds/versions pinned for the… → …
- Hardening an ICRA papers reproducibility — specifying robot platform
- SKILL.md covers The specification ledger, Logging: the rosbag is the lab…, Determinism where it exists,… and Release scaffold, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Icra Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when hardening an ICRA paper's reproducibility — specifying robot platform, firmware, ROS and driver versions, control rates, and sensor calibration; logging rosbags and seeds; separating what others can rerun (code, sim) from what they can only audit (your hardware trials); and writing honest availability statements.
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.
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
- Hardening an ICRA papers reproducibility — specifying robot platform
- ROS and driver versions
- Sensor calibration
- Logging rosbags and seeds
Example prompts
- “/icra-reproducibility”
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Specification ledger complete in-paper (table above, compressed)?
- Every reported number regenerates from logs via one documented command?
- Seeds/versions pinned for the deterministic tier; container builds clean?
- Hardware protocol written so a stranger could run trial 1 tomorrow?
- Release scaffold anonymized; links leak-checked?
- Availability statement matches what actually exists today?
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
Icra Reproducibility loads about 1.6k tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 662 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). 662 words, ~1,574 tokens.
Download SKILL.mdSave it as
.claude/skills/icra-reproducibility/SKILL.md (or your agent's skills folder).- name
- icra-reproducibility
- description
- Use when hardening an ICRA paper's reproducibility — specifying robot platform, firmware, ROS and driver versions, control rates, and sensor calibration; logging rosbags and seeds; separating what others can rerun (code, sim) from what they can only audit (your hardware trials); and writing honest availability statements.
ICRA Reproducibility
Reproducibility at a robotics conference means something different than at an ML venue: no reader can rerun your hardware trials without your robot, your room, and your objects. The achievable standard is therefore two-tier — rerunnable (code, simulation, analysis) and auditable (hardware evidence logged well enough that a skeptic can verify you did what you claim). ICRA papers earn trust by being explicit about which tier each result sits in.
The specification ledger
A robotics result is unreproducible if the platform is underspecified. The paper (body, since there is no appendix escape) plus released materials should pin:
| Layer | Must specify | Example of "enough" |
|---|---|---|
| Robot | model, DOF, payload, firmware version | "UR5e, PolyScope 5.11" |
| End effector | model, mods, wear state if relevant | "Robotiq 2F-85, stock pads" |
| Sensors | model, resolution, rate, mounting frame | "D435i @ 640×480, 30 Hz, wrist" |
| Compute | on-board vs off-board, GPU, latency path | "off-board 3080, 5G-free wired" |
| Middleware | ROS distro, key package versions | "ROS 2 Humble, MoveIt 2.5.4" |
| Control | loop rates, gains or their source | "impedance @ 500 Hz, gains in repo" |
| Calibration | method + residual error | "hand-eye via [ref], 1.8 mm RMS" |
| Objects/scenes | identity, source, dimensions | "YCB subset listed in Tab. II" |
Standard object sets (YCB and similar) exist precisely so that "graspable household objects" can be a checkable claim; use them or publish the object specs.
Logging: the rosbag is the lab notebook
- Record every hardware session — including failed ones — with topic-complete rosbags (or vendor-equivalent logs) plus an untouched camera view.
- One log per trial, named by protocol:
trial_<cond>_<idx>_<date>.bag; the analysis pipeline should consume these logs, so paper numbers regenerate from raw data with one command. - Keep a session sheet: date, operator, firmware state, anomalies. Two months later, this distinguishes "the gripper was recalibrated between Tables II and III" from unexplainable drift.
- The video attachment should be cut from these recorded sessions, which guarantees footage corresponds to logged, reported trials.
Determinism where it exists, honesty where it doesn't
Hardware trials are not seed-reproducible — contact, cables, lighting, and thermal drift see to that. Split the claims accordingly:
- Deterministic tier: training runs, simulation experiments, and analysis scripts get pinned seeds, pinned dependency versions, and containerized environments. State seeds and repetition counts.
- Stochastic tier: hardware trials get protocol reproducibility — the documented procedure another lab could follow — plus dispersion reporting.
- Never write "results are fully reproducible" over a hardware table; write "code and simulation reproduce Tables I-II; hardware protocol and logs for Tables III-IV are released for audit."
Show full SKILL.md (258 more words)Show less
Release scaffold
repo/
├── README.md # claim → command map (Table III = run_hw_analysis.sh)
├── env/ # Dockerfile or rosdep/lockfiles, pinned
├── sim/ # simulation experiments, seeds fixed
├── control/ # controllers/planners as ROS packages
├── hw_protocol.md # step-by-step trial procedure, success criterion,
│ # reset procedure, safety notes
├── logs/ # rosbags or download script (size!), session sheets
├── analysis/ # regenerates every figure/table from logs/
└── video/ # raw clips ↔ trial IDs mappingAnonymize the repository for review under the double-anonymous policy (2026
cycle onward): anonymized hosting or an artifact stripped of names — an org URL
is an identity leak (see icra-submission).
Compute and latency reporting
Robotics adds a real-time dimension absent from ML reproducibility norms:
- Report where each computation ran (on-board CPU/embedded GPU vs off-board workstation) and the link between them; an off-board 3090 over gigabit wire is a materially different system than on-board inference.
- State end-to-end latency per pipeline stage (sensing → perception → decision → actuation) at least once; "runs in real time" is unverifiable without it.
- Training compute (GPU-hours, hardware) belongs in the paper for learned components — cheap to report, increasingly expected by review forms.
Availability statement patterns
Honest, specific statements outperform boilerplate promises:
- "Code, simulation environments, and trial logs:
<link>(anonymized for review; public on acceptance)." - "The gripper design files are released; the arm is commercial (UR5e)."
- "Raw rosbags total 1.2 TB; per-trial extracted features and a 40 GB sample are hosted, full logs on request."
- Avoid: "code will be released upon publication" with nothing at review time — reviewers discount unverifiable promises, and some cycles ask availability questions directly on the review form (verify the current form).
Pre-submission reproducibility pass
- Specification ledger complete in-paper (table above, compressed)?
- Every reported number regenerates from logs via one documented command?
- Seeds/versions pinned for the deterministic tier; container builds clean?
- Hardware protocol written so a stranger could run trial 1 tomorrow?
- Release scaffold anonymized; links leak-checked?
- Availability statement matches what actually exists today?
Output format
[Tier split] rerunnable: <tables/figs> | auditable: <tables/figs>
[Spec ledger] missing rows: <list or none>
[Log coverage] trials logged <n>/<n>, analysis regenerates: y/n
[Determinism] seeds/versions pinned for sim+training: y/n
[Release] scaffold complete? anonymized? size plan?
[Statement] honest-specific / boilerplate-risk — rewrite: <line>© 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-reproducibility of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Icra 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 |
|---|---|---|---|---|---|---|
| Icra Reproducibility this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.6k | 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 Icra Reproducibility
What does Icra Reproducibility do?
A skill your agent uses when hardening an ICRA paper's reproducibility — specifying robot platform, firmware, ROS and driver versions, control rates, and sensor calibration; logging rosbags and…. Icra Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when hardening an ICRA paper's reproducibility — specifying robot platform, firmware, ROS and driver versions, control rates, and sensor calibration; logging rosbags and seeds; separating what others can rerun (code, sim) from what they can only audit (your hardware trials); and writing honest availability statements.
When should I use Icra Reproducibility?
Icra Reproducibility fits situations like: hardening an ICRA papers reproducibility — specifying robot platform; ROS and driver versions; sensor calibration; logging rosbags and seeds.
How do I install Icra Reproducibility in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icra-reproducibility -a claude-code`. Or copy the skill folder (ICRA-Skills/skills/icra-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/icra-reproducibility in your project. Claude Code loads it when a task matches its description.
How do I install Icra Reproducibility in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icra-reproducibility -a codex`. Or copy the skill folder (ICRA-Skills/skills/icra-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/icra-reproducibility in your project. Codex loads it when a task matches its description.
Can I use Icra 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 icra-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/icra-reproducibility, .gemini/skills/icra-reproducibility, .github/skills/icra-reproducibility and .opencode/skills/icra-reproducibility in your project.
What does Icra Reproducibility need to run?
SKILL.md names no scripts, command-line tools or credentials: Icra Reproducibility is instructions for the agent only.
Does Icra 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 Icra 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 Icra Reproducibility use?
Icra 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 Icra Reproducibility 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 Reproducibility?
Skills that share tags, products or a category with Icra 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 Icra 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.