Peer Review
spacering-net/codeg
Structured manuscript/grant review with checklist-based evaluation.
A skill your agent uses when reasoning about how SIGIR evaluates submissions — the per-track OpenReview machinery, double-blind full/short review versus single-anonymous Resources review, the…
Install Sigir Review Process
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigir-review-process -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigir-review-process --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/SIGIR-Skills/skills/sigir-review-process .claude/skills/sigir-review-process && 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 "sigir-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGIR-Skills/skills/sigir-review-process into .claude/skills/sigir-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigir-review-process", 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/SIGIR-Skills/skills/sigir-review-processType 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 sigir-review-process -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigir-review-process --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/SIGIR-Skills/skills/sigir-review-process .agents/skills/sigir-review-process && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "sigir-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGIR-Skills/skills/sigir-review-process into .agents/skills/sigir-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigir-review-process", 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 sigir-review-process -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigir-review-process --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/SIGIR-Skills/skills/sigir-review-process .cursor/skills/sigir-review-process && 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 "sigir-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGIR-Skills/skills/sigir-review-process into .cursor/skills/sigir-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigir-review-process", 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 SIGIR-Skills/skills/sigir-review-process--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 sigir-review-process -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills sigir-review-process --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/SIGIR-Skills/skills/sigir-review-process .gemini/skills/sigir-review-process && 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 "sigir-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGIR-Skills/skills/sigir-review-process into .gemini/skills/sigir-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigir-review-process", 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 sigir-review-processInstalls 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 sigir-review-process -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/SIGIR-Skills/skills/sigir-review-process .github/skills/sigir-review-process && 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 "sigir-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGIR-Skills/skills/sigir-review-process into .github/skills/sigir-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigir-review-process", 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 sigir-review-process -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 sigir-review-process --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/SIGIR-Skills/skills/sigir-review-process .opencode/skills/sigir-review-process && 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 "sigir-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGIR-Skills/skills/sigir-review-process into .opencode/skills/sigir-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sigir-review-process", 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
sigir-review-process- GitHub stars
- 1.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 682 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when reasoning about how SIGIR evaluates submissions — the per-track OpenReview machinery, double-blind full/short review versus single-anonymous Resources review, the…
- Works in 5 steps: Is the comparison fair? (Tuned… → Are the differences real? (Paired… → Is the metric-task pairing sound?… → …
- Reasoning about how SIGIR evaluates submissions — the per-track OpenReview machinery
- SKILL.md covers The machinery, What SIGIR reviewers actually…, Reviewer archetypes and what… and Reading a decision packet, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Sigir Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when reasoning about how SIGIR evaluates submissions — the per-track OpenReview machinery, double-blind full/short review versus single-anonymous Resources review, the PC-member nomination duty, what IR reviewers score (evaluation validity above novelty claims), the ACM Peer Review Policy layer, and how decisions land.
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 Peer review. 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
- Reasoning about how SIGIR evaluates submissions — the per-track OpenReview machinery
- Double-blind full/short review versus single-anonymous Resources review
- The PC-member nomination duty
- What IR reviewers score (evaluation validity above novelty claims)
Example prompts
- “/sigir-review-process”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Is the comparison fair? (Tuned baselines, same collections, same qrels, same
- Are the differences real? (Paired significance tests, multiple-comparison
- Is the metric-task pairing sound? (nDCG@10 for ad-hoc ranking, recall for
- Does the mechanism explain the gain? (Ablations that isolate the claimed source.)
- Only then: how novel is the idea, and how broadly does it matter?
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
Sigir Review Process loads about 1.6k tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 682 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). 682 words, ~1,634 tokens.
Download SKILL.mdSave it as
.claude/skills/sigir-review-process/SKILL.md (or your agent's skills folder).- name
- sigir-review-process
- description
- Use when reasoning about how SIGIR evaluates submissions — the per-track OpenReview machinery, double-blind full/short review versus single-anonymous Resources review, the PC-member nomination duty, what IR reviewers score (evaluation validity above novelty claims), the ACM Peer Review Policy layer, and how decisions land.
SIGIR Review Process
SIGIR review is track-partitioned: each track (full, short, resources, reproducibility, perspectives, industry, ...) runs its own OpenReview group with its own reviewer pool, anonymity regime, and calendar. Advice that treats "SIGIR review" as one process misroutes authors. This skill models the machinery and the reviewer psychology; exact per-cycle mechanics (rebuttal windows, score scales, meta-review forms) were not publicly verifiable for 2026 and must be read off your own submission's OpenReview timeline (待核实).
The machinery
| Element | What was verified for 2026 | What to confirm per cycle |
|---|---|---|
| Platform | OpenReview, per-track venue groups | Group id for your track |
| Full/short anonymity | Double-blind, fully anonymized | Preprint policy details |
| Resources anonymity | Single-anonymous (reviewers see authors) | — |
| Reviewer sourcing | Full-paper teams nominate one author as PC member per submission | Whether shorts/other tracks share the duty |
| Policy layer | ACM Peer Review Policy; automated compliance checks reserved | Cycle-specific screening tools |
| Decision structure | Not extractable | Rebuttal? meta-reviews? conditional accepts? |
The PC-nomination duty has a strategic edge authors miss: your nominated author will review other SIGIR submissions during your own paper's review window. Nominate someone senior enough to review credibly — chairs notice teams that nominate their most junior author, and review quality is a community reputation signal.
What SIGIR reviewers actually score
Across editions, IR reviewing culture weighs evaluation validity above almost everything. The informal reviewer checklist, reverse-engineered from the field's own methodology literature:
- Is the comparison fair? (Tuned baselines, same collections, same qrels, same metric implementations.)
- Are the differences real? (Paired significance tests, multiple-comparison handling, variance across seeds for neural systems.)
- Is the metric-task pairing sound? (nDCG@10 for ad-hoc ranking, recall for first-stage retrieval, judged@k when pools are shallow.)
- Does the mechanism explain the gain? (Ablations that isolate the claimed source.)
- Only then: how novel is the idea, and how broadly does it matter?
The consequence: at SIGIR a modest idea with airtight evaluation routinely outscores a bold idea with a shaky one. Papers written novelty-first, evidence-second read as misrouted ML-venue submissions.
Reviewer archetypes and what convinces each
- The evaluation methodologist: reads §Experiments first; convinced by protocol symmetry and correct statistics; enraged by copied baseline numbers.
- The systems pragmatist: asks what it costs; convinced by latency/index-size tables; suspicious of quality wins that ignore efficiency entirely.
- The task veteran: knows the collection's quirks and every prior result on it; convinced by correct positioning against the collection's known ceiling effects.
- The user-focused skeptic: asks whether the offline gain would survive contact with users; softened by honest scope statements about offline evaluation limits.
A submission cannot satisfy all four maximally in 9 pages; it must avoid offending any of them (the four standing objections: unfair tuning, no significance testing, metric mismatch, unexplained mechanism).
Show full SKILL.md (236 more words)Show less
Reading a decision packet
Decision-packet triage
----------------------
1. Sort claims-about-your-paper into: factual error / evidence gap / scope dispute.
2. Factual errors -> correction with coordinates (if a channel exists; see
sigir-author-response).
3. Evidence gaps named by >=2 reviewers -> real; plan the experiment, not the reply.
4. Scope disputes ("should have tested on X") -> decide if X is load-bearing for
the claim as written; narrow the claim or add X, never argue taste.
5. Extract every "the authors should ..." into the next-version checklist verbatim.Reading scores like a chair
Without the cycle's exact scale (待核实), read shapes rather than numbers:
- Converging middling scores with the same named gap = a real, fixable defect; the packet is a work order.
- High variance (one champion, one detractor) = the paper's framing lets two archetypes read different papers; the fix is usually §1, not §5.
- Uniform low confidence = the submission landed outside the track's reviewer
pool; re-read
sigir-topic-selectionbefore blaming reviewers. - A long, detailed negative review is the most valuable object in the packet — it is the only reviewer who fully engaged; answer it with matching precision.
Confidentiality and conduct
- Submissions are confidential under the ACM Peer Review Policy: reviewers must not share, reuse, or feed submissions to external services; authors likewise must not publicize reviewer text out of context.
- Attempting to identify reviewers, or contacting suspected reviewers about a live submission, is a conduct violation with career-scale downside in a community this small — every senior IR researcher reviews for SIGIR eventually.
- Suspected review misconduct (plagiarized review, LLM-generated boilerplate, conflict violations) goes to the track chairs through official channels only.
After the decision
- Accept: conditional items (if any) become the first camera-ready tasks; see
sigir-camera-ready. - Reject: the packet is a specification for the next venue; the SIGIR-family
calendar (next SIGIR, SIGIR-AP, ECIR, CIKM, WSDM) means a well-revised paper waits
months, not a year — see
sigir-workflowfor the routing calendar.
Output format
[Track machinery] group id / anonymity regime / nomination duty satisfied
[Standing-objection audit] tuning-fairness / significance / metric-match / mechanism: pass-risk each
[Archetype exposure] which reviewer archetype the paper most risks offending
[Packet triage] factual errors <n> / evidence gaps <n> / scope disputes <n>
[Confidentiality flags] none / <issue to raise with chairs>
[Next move] respond / revise-for-<venue> / camera-ready© 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 SIGIR-Skills/skills/sigir-review-process of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Sigir Review Process 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 |
|---|---|---|---|---|---|---|
| Sigir Review Process this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Peer Reviewspacering-net/codeg | 3.9k | 17 repos | ~5.9k | Automated safety check: Notes | MIT | |
| Scholar Evaluationspacering-net/codeg | 3.9k | 11 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Academic Paper Writing PipelineImbad0202/academic-research-skills | 51k | — | ~16k | Automated safety check: Pass | Custom licence | |
| Academic Paper ReviewerImbad0202/academic-research-skills | 51k | — | ~11k | Automated safety check: Pass | Custom licence | |
| Peer ReviewK-Dense-AI/claude-scientific-writer | 2.4k | 2 repos | ~3.1k | Automated safety check: Notes | MIT |
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Peer Review
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Questions about Sigir Review Process
What does Sigir Review Process do?
A skill your agent uses when reasoning about how SIGIR evaluates submissions — the per-track OpenReview machinery, double-blind full/short review versus single-anonymous Resources review, the…. Sigir Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when reasoning about how SIGIR evaluates submissions — the per-track OpenReview machinery, double-blind full/short review versus single-anonymous Resources review, the PC-member nomination duty, what IR reviewers score (evaluation validity above novelty claims), the ACM Peer Review Policy layer, and how decisions land.
When should I use Sigir Review Process?
Sigir Review Process fits situations like: reasoning about how SIGIR evaluates submissions — the per-track OpenReview machinery; double-blind full/short review versus single-anonymous Resources review; the PC-member nomination duty; what IR reviewers score (evaluation validity above novelty claims).
How do I install Sigir Review Process in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigir-review-process -a claude-code`. Or copy the skill folder (SIGIR-Skills/skills/sigir-review-process in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/sigir-review-process in your project. Claude Code loads it when a task matches its description.
How do I install Sigir Review Process in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigir-review-process -a codex`. Or copy the skill folder (SIGIR-Skills/skills/sigir-review-process in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/sigir-review-process in your project. Codex loads it when a task matches its description.
Can I use Sigir Review Process 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 sigir-review-process -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sigir-review-process, .gemini/skills/sigir-review-process, .github/skills/sigir-review-process and .opencode/skills/sigir-review-process in your project.
What does Sigir Review Process need to run?
SKILL.md names no scripts, command-line tools or credentials: Sigir Review Process is instructions for the agent only.
Does Sigir Review Process 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 Sigir Review Process 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 Sigir Review Process use?
Sigir Review Process 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 Sigir Review Process use?
About 1.6k tokens (SKILL.md is roughly 6.5k 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 Sigir Review Process?
Skills that share tags, products or a category with Sigir Review Process: Peer Review (spacering-net/codeg, 3.9k stars), Scholar Evaluation (spacering-net/codeg, 3.9k stars), Academic Paper Writing Pipeline (Imbad0202/academic-research-skills, 51k stars) and Academic Paper Reviewer (Imbad0202/academic-research-skills, 51k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sigir Review Process?
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.