Peer Review
K-Dense-AI/claude-scientific-writer
Prepare evidence-bounded, constructive peer-review drafts and structured manuscript assessments.
A skill your agent uses when strengthening reproducibility for an ICDM (IEEE International Conference on Data Mining) paper - seeds, configs, compute and data reporting, and an anonymized…
Install Icdm Reproducibility
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icdm-reproducibility -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icdm-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/ICDM-Skills/skills/icdm-reproducibility .claude/skills/icdm-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 "icdm-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICDM-Skills/skills/icdm-reproducibility into .claude/skills/icdm-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icdm-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/ICDM-Skills/skills/icdm-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 icdm-reproducibility -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icdm-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/ICDM-Skills/skills/icdm-reproducibility .agents/skills/icdm-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 "icdm-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICDM-Skills/skills/icdm-reproducibility into .agents/skills/icdm-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icdm-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 icdm-reproducibility -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icdm-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/ICDM-Skills/skills/icdm-reproducibility .cursor/skills/icdm-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 "icdm-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICDM-Skills/skills/icdm-reproducibility into .cursor/skills/icdm-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icdm-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 ICDM-Skills/skills/icdm-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 icdm-reproducibility -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icdm-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/ICDM-Skills/skills/icdm-reproducibility .gemini/skills/icdm-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 "icdm-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICDM-Skills/skills/icdm-reproducibility into .gemini/skills/icdm-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icdm-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 icdm-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 icdm-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/ICDM-Skills/skills/icdm-reproducibility .github/skills/icdm-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 "icdm-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICDM-Skills/skills/icdm-reproducibility into .github/skills/icdm-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icdm-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 icdm-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 icdm-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/ICDM-Skills/skills/icdm-reproducibility .opencode/skills/icdm-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 "icdm-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICDM-Skills/skills/icdm-reproducibility into .opencode/skills/icdm-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icdm-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
icdm-reproducibility- GitHub stars
- 1.2k
- Token cost
- ~1.1k tokens
- SKILL.md length
- 435 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when strengthening reproducibility for an ICDM (IEEE International Conference on Data Mining) paper - seeds, configs, compute and data reporting, and an anonymized…
- Strengthening reproducibility for an ICDM (IEEE International Conference on Data Mining) paper - seeds
- SKILL.md covers What must be reproducible, Reproducibility tiers, Configs as artifacts and Triple-blind the package, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Compute and data reporting
What it does
Icdm Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when strengthening reproducibility for an ICDM (IEEE International Conference on Data Mining) paper - seeds, configs, compute and data reporting, and an anonymized reproduction package that survives the Research Track's triple-blind regime while every detail fights for room inside the single 10-page IEEE all-inclusive cap.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Research & Science, covering Reproducible research. 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 reproducibility for an ICDM (IEEE International Conference on Data Mining) paper - seeds
- Compute and data reporting
Example prompts
- “/icdm-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 (its code samples are yaml).
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
Icdm Reproducibility loads about 1.1k tokens when it runs. Until then it costs about 87 tokens; SKILL.md has 435 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). 435 words, ~1,077 tokens.
Download SKILL.mdSave it as
.claude/skills/icdm-reproducibility/SKILL.md (or your agent's skills folder).- name
- icdm-reproducibility
- description
- Use when strengthening reproducibility for an ICDM (IEEE International Conference on Data Mining) paper - seeds, configs, compute and data reporting, and an anonymized reproduction package that survives the Research Track's triple-blind regime while every detail fights for room inside the single 10-page IEEE all-inclusive cap.
ICDM Reproducibility
Make the mining result reproducible as science, under two ICDM-specific pressures: the Research Track is triple-blind, so the reproduction package cannot reveal identity, and the reporting all competes for space inside the 10-page all-inclusive cap. Reproducibility at ICDM is not a separate checklist form (verify per edition); it is evidence that the discovery is real rather than a lucky configuration.
What must be reproducible
- The mining task setup: exact datasets, versions, preprocessing, splits, and how ground truth or injections were generated.
- The method: hyperparameters, model selection procedure, the mechanism's knobs (e.g. sketch size, partition count), and the random seeds.
- The evaluation: metrics, thresholds/cutoffs, variance estimation, and the hardware behind any timing claim.
Reproducibility tiers
| Tier | What a reviewer can do | How to reach it |
|---|---|---|
| Rerunnable | Re-execute your scripts and get your tables | Pinned deps, seeds, config files, entry script |
| Rebuildable | Reconstruct the pipeline from description alone | Precise protocol in the paper + appendix |
| Attested | Trust numbers that cannot be shared (private data) | Documented protocol + synthetic proxy + honest scope |
Aim for rerunnable on any public-data result; use attested only where data genuinely cannot be released, and say so plainly.
Configs as artifacts
Put the run behind a config, not scattered command-line flags, so a reviewer reproduces a table by pointing at a file.
# repro/config.yaml (anonymized; no author paths, no institutional dataset names)
task: stream_anomaly_ranking
dataset: public_edge_stream_v3 # public source + version, not an internal name
seeds: [0, 1, 2, 3, 4, ... , 19] # the 20 seeds behind the reported variance
method:
sketch_partitions: 128 # the mechanism knob mapped in the ablation
hash_family: multiplicative
eval:
metric: precision_at_k
k: 100
time_respecting_split: true
compute:
hardware: "1x consumer GPU, 16GB" # generic; states the basis of any timing claimTriple-blind the package
- Export a fresh repository with no git history — commit metadata routinely leaks author names and institutions.
- Remove author paths, usernames, internal dataset names, cluster hostnames, and README acknowledgements.
- Host it so the link in the PDF resolves to an anonymized location, not a named account.
- Because ICDM traditionally offers no rebuttal, this package is often the only extra evidence a reviewer ever sees — it must be complete and anonymous at submission time.
Show full SKILL.md (147 more words)Show less
Report inside the page cap
- The full reproduction protocol can live in an in-cap appendix and the cited repository; the body must still state seeds, key hyperparameters, and the compute basis of timing claims.
- Prefer a compact reproducibility paragraph plus a repository over a sprawling appendix that eats pages the body needs.
Vignette: the seed table that answered a review before it was written
A team worried reviewers would read their close margins as noise. Rather than hope for a rebuttal that ICDM might not offer, they reported every metric with a standard deviation over 20 seeds, shipped the seed list and configs in an anonymized, history-scrubbed repository cited in the PDF, and stated the exact GPU behind their latency numbers. The "is this just noise?" review never came, because the paper had already answered it — and nothing in the package revealed who they were.
Output format
[Repro tier] rerunnable / rebuildable / attested (per result)
[Seeds+variance] reported: yes / no
[Config-as-artifact] present: yes / no
[Anonymized package] history-scrubbed + no institutional names: yes / leaks found
[Compute basis] hardware behind timing claims stated: yes / no
[Top gap] <single most important missing reproducibility detail>© 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 ICDM-Skills/skills/icdm-reproducibility of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Icdm 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 |
|---|---|---|---|---|---|---|
| Icdm Reproducibility this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.1k | Automated safety check: Pass | MIT | |
| 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 | |
| Add Bactopia Toolbactopia/bactopia | 522 | — | ~4.1k | Automated safety check: Pass | MIT |
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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/.
Modeling Code and Result Contracts
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Generates result-evidence contracts, tables and runnable q1 to q3 modeling code scaffolds for a math modeling paper from a model route, a data plan and cleaned data.
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Categories
Questions about Icdm Reproducibility
What does Icdm Reproducibility do?
A skill your agent uses when strengthening reproducibility for an ICDM (IEEE International Conference on Data Mining) paper - seeds, configs, compute and data reporting, and an anonymized…. Icdm Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when strengthening reproducibility for an ICDM (IEEE International Conference on Data Mining) paper - seeds, configs, compute and data reporting, and an anonymized reproduction package that survives the Research Track's triple-blind regime while every detail fights for room inside the single 10-page IEEE all-inclusive cap.
When should I use Icdm Reproducibility?
Icdm Reproducibility fits situations like: strengthening reproducibility for an ICDM (IEEE International Conference on Data Mining) paper - seeds; compute and data reporting.
How do I install Icdm Reproducibility in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icdm-reproducibility -a claude-code`. Or copy the skill folder (ICDM-Skills/skills/icdm-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/icdm-reproducibility in your project. Claude Code loads it when a task matches its description.
How do I install Icdm Reproducibility in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icdm-reproducibility -a codex`. Or copy the skill folder (ICDM-Skills/skills/icdm-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/icdm-reproducibility in your project. Codex loads it when a task matches its description.
Can I use Icdm 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 icdm-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/icdm-reproducibility, .gemini/skills/icdm-reproducibility, .github/skills/icdm-reproducibility and .opencode/skills/icdm-reproducibility in your project.
What does Icdm Reproducibility need to run?
SKILL.md names no scripts, command-line tools or credentials: Icdm Reproducibility is instructions for the agent only.
Does Icdm 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 Icdm 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 Icdm Reproducibility use?
Icdm 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 Icdm Reproducibility use?
About 1.1k tokens (SKILL.md is roughly 4.3k 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 Icdm Reproducibility?
Skills that share tags, products or a category with Icdm Reproducibility: Peer Review (K-Dense-AI/claude-scientific-writer, 2.4k stars), CHARLS Paper Reproduction Guide (xjtulyc/MedgeClaw, 617 stars), Compute Environment Setup (aipoch/open-science, 5.5k stars) and Figure Style (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 Icdm 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.