Decide
alirezarezvani/claude-skills
/cs:decide <memo — Log a decision to two-layer memory via decision-logger.
A skill your agent uses when reasoning about how WSDM reviews and decides papers - the hybrid single/double-blind architecture with Associate-Chair metadata visibility, at-least-three PC reviews…
MITAuto-check passed
Install Wsdm Review Process
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill wsdm-review-process -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills wsdm-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/WSDM-Skills/skills/wsdm-review-process .claude/skills/wsdm-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 "wsdm-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/WSDM-Skills/skills/wsdm-review-process into .claude/skills/wsdm-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wsdm-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/WSDM-Skills/skills/wsdm-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 wsdm-review-process -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills wsdm-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/WSDM-Skills/skills/wsdm-review-process .agents/skills/wsdm-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 "wsdm-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/WSDM-Skills/skills/wsdm-review-process into .agents/skills/wsdm-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wsdm-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 wsdm-review-process -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills wsdm-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/WSDM-Skills/skills/wsdm-review-process .cursor/skills/wsdm-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 "wsdm-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/WSDM-Skills/skills/wsdm-review-process into .cursor/skills/wsdm-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wsdm-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 WSDM-Skills/skills/wsdm-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 wsdm-review-process -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills wsdm-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/WSDM-Skills/skills/wsdm-review-process .gemini/skills/wsdm-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 "wsdm-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/WSDM-Skills/skills/wsdm-review-process into .gemini/skills/wsdm-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wsdm-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 wsdm-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 wsdm-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/WSDM-Skills/skills/wsdm-review-process .github/skills/wsdm-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 "wsdm-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/WSDM-Skills/skills/wsdm-review-process into .github/skills/wsdm-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wsdm-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 wsdm-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 wsdm-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/WSDM-Skills/skills/wsdm-review-process .opencode/skills/wsdm-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 "wsdm-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/WSDM-Skills/skills/wsdm-review-process into .opencode/skills/wsdm-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wsdm-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
wsdm-review-process- GitHub stars
- 1.2k
- Token cost
- ~1.7k tokens
- SKILL.md length
- 753 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 WSDM reviews and decides papers - the hybrid single/double-blind architecture with Associate-Chair metadata visibility, at-least-three PC reviews…
- Reasoning about how WSDM reviews and decides papers - the hybrid single/double-blind architecture with Associate-Chair metadata visibility
- SKILL.md covers The pipeline, Who sees what: the…, Reading the reviewer pool and No rebuttal: decision dynamics, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- At-least-three PC reviews plus senior PC assessment
What it does
Wsdm Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when reasoning about how WSDM reviews and decides papers - the hybrid single/double-blind architecture with Associate-Chair metadata visibility, at-least-three PC reviews plus senior PC assessment, the absence of a rebuttal phase, the August-to-October window, and what ~17% selectivity at a single-track venue implies.
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的… The licence is MIT.
When your agent uses it
- Reasoning about how WSDM reviews and decides papers - the hybrid single/double-blind architecture with Associate-Chair metadata visibility
- At-least-three PC reviews plus senior PC assessment
- The absence of a rebuttal phase
- The August-to-October window
Example prompts
- “/wsdm-review-process”
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
Wsdm Review Process loads about 1.7k tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 753 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). 753 words, ~1,705 tokens.
Download SKILL.mdSave it as
.claude/skills/wsdm-review-process/SKILL.md (or your agent's skills folder).- name
- wsdm-review-process
- description
- Use when reasoning about how WSDM reviews and decides papers - the hybrid single/double-blind architecture with Associate-Chair metadata visibility, at-least-three PC reviews plus senior PC assessment, the absence of a rebuttal phase, the August-to-October window, and what ~17% selectivity at a single-track venue implies.
WSDM Review Process
Model the machinery that turns an August submission into an October decision. Understanding it changes writing decisions months earlier, because WSDM's process has two properties that most neighboring venues lack: authors never get to reply, and the venue's blinding design is unusually explicit about who sees what. Process details are re-set by each edition's chairs - the 2026-cycle anchors below are for calibration, not prediction.
The pipeline
Aug 7 abstract registered -> bidding/assignment signal for the PC
Aug 14 full paper (AoE) -> desk screening (format, scope, anonymity,
ethics section present)
Aug-Oct at least 3 PC reviews -> written independently; no author contact
+ senior PC (SPC) -> meta-assessment, consensus-building
Associate Chairs -> see metadata incl. authorship, manage COI
Oct 23 notification (2026 anchor)
camera-ready + ACM production (dates 待核实 per edition)
Feb single-track conferenceRoughly ten weeks from paper to decision - among the fastest of the major mining venues, which is precisely why there is no room for a rebuttal round.
Who sees what: the hybrid-blind design
The 2025 and 2026 CFPs describe "a combination of single-blind reviewing and double-blind reviewing": reviewers and SPCs get anonymized PDFs; Associate Chairs see submission metadata, including authorship, to detect undisclosed conflicts. Implications for authors:
- Your scientific evaluators judge the anonymized artifact only. All the
self-containment and anonymization discipline of
wsdm-submissionexists for their benefit. - The metadata layer is an integrity mechanism, not a reputational one - it does not transmit prestige to the people scoring you.
- This design is historically literate: WSDM 2017 hosted the controlled experiment (Tomkins, Zhang & Heavlin, published in PNAS 2017) in which single-blind reviewers bid more on and rated more favorably the papers of famous authors and top institutions. The venue then engineered a process that keeps scoring blind while still policing conflicts. Expect chairs to take anonymity breaches personally; the policy is theirs by conviction.
Reading the reviewer pool
WSDM's PC blends academic IR/mining researchers with industry scientists from search, recommendation, and ads groups - the conference was founded as, and markets itself as, the venue where "practical yet principled" work lives. Consequences:
| Reader | What convinces them | What loses them |
|---|---|---|
| Academic IR/mining reviewer | Clean formalization, bias-aware offline evaluation, strong recent baselines | Undefined novelty over last year's WSDM/SIGIR papers |
| Industry reviewer | Data realism, latency/cost awareness, deployment plausibility | Toy datasets presented as web-scale; ignoring serving constraints |
| SPC (writes the meta-review) | Consistency across claims, evidence, limitations | One overclaimed sentence that a reviewer flags and the paper never defends |
Write for the intersection: every headline claim should survive both the "is it sound?" and the "would it survive contact with a platform?" reads.
No rebuttal: decision dynamics
With no author input after submission, disagreement resolution happens between reviewers and the SPC. Practical consequences:
- A single confident negative review carries more terminal weight than at
rebuttal venues, because you cannot dilute it with a reply. The counter is
preemptive: the objection-inventory method in
wsdm-author-response. - Borderline papers live or die on the SPC's reading of whether weaknesses are fixable presentation issues or structural flaws. Make fixability visible: explicit limitation paragraphs signal self-awareness and give the SPC language to defend the paper.
- Reviews arrive as feedback for the next venue. Their consensus items are the revision contract; their misreadings are your ambiguity bugs.
Show full SKILL.md (282 more words)Show less
Decoding review language after notification
Because no dialogue ever occurred, WSDM reviews compress judgments into stock phrases. A translation layer for triage (heuristics, not officialdom):
- "The evaluation does not control for..." - a validity-quadrant hit; at this venue this is usually the decisive sentence in the packet.
- "The contribution is incremental over [WSDM/SIGIR paper]" - a lineage
positioning failure more often than a novelty failure; check whether your
contrast sentence for that exact paper existed (
wsdm-related-work). - "Unclear whether this would work in practice" - the industry read rejected the setting's realism; the fix is data-regime honesty, not more benchmarks.
- "Well written but I am not convinced of the significance" - the choose-this-paper test failed; the work may be short-track shaped.
- Three lukewarm-positive reviews and a rejection - normal at one-in-six selectivity with fixed program capacity; read the SPC's meta-review for the actual ranking rationale before blaming any reviewer.
Selectivity arithmetic
2025 anchor: more than 600 submissions, just over 100 acceptances (~16-17%). Single-track scheduling caps how many talks the program can hold, so acceptance volume does not stretch with submission growth the way multi-track venues absorb it. Strategic readings:
- "Solid but unremarkable" occupies the rejection region: at one-in-six, papers need a reason to be chosen, not merely no reason to be rejected.
- The short-paper track (new since 2026) is the pressure valve for focused contributions that cannot win a long-paper slot on breadth.
- Deadlines are annual: a rejection costs twelve months at this venue, which makes the pre-submission adversarial pass cheap by comparison.
- Selectivity plus a compact PC also means repeat encounters: the reviewer pool sees your resubmission next year. Papers that visibly absorbed last year's reviews start ahead; papers that ignored them start behind zero.
Output format
[Cycle model] deadlines / notification / process confirmed from current CFP: <list + gaps>
[Blinding] hybrid design implications applied to this paper: <notes>
[Pool coverage] academic read / industry read / SPC read: convinced or at-risk
[Terminal-review risk] strongest single objection with no in-PDF answer: <item>
[Selectivity call] long paper / short paper / different venue, with reason© 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 WSDM-Skills/skills/wsdm-review-process of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Wsdm 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 |
|---|---|---|---|---|---|---|
| Wsdm Review Process this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.7k | Automated safety check: Pass | MIT | |
| Decidealirezarezvani/claude-skills | 28k | — | ~871 | Automated safety check: Pass | MIT | |
| Papers Skillsickn33/agentic-awesome-skills | 47k | 1 repos | ~2.1k | Automated safety check: Pass | MIT | |
| Deepseek Reasonruvnet/ruflo | 74k | — | ~626 | Automated safety check: Notes | MIT | |
| Read arXiv Paperkarpathy/nanochat | 59k | 1 repos | ~494 | Automated safety check: Pass | MIT | |
| Hugging Face Paper Pageshuggingface/skills | 11k | 3 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 |
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Questions about Wsdm Review Process
What does Wsdm Review Process do?
A skill your agent uses when reasoning about how WSDM reviews and decides papers - the hybrid single/double-blind architecture with Associate-Chair metadata visibility, at-least-three PC reviews…. Wsdm Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when reasoning about how WSDM reviews and decides papers - the hybrid single/double-blind architecture with Associate-Chair metadata visibility, at-least-three PC reviews plus senior PC assessment, the absence of a rebuttal phase, the August-to-October window, and what ~17% selectivity at a single-track venue implies.
When should I use Wsdm Review Process?
Wsdm Review Process fits situations like: reasoning about how WSDM reviews and decides papers - the hybrid single/double-blind architecture with Associate-Chair metadata visibility; at-least-three PC reviews plus senior PC assessment; the absence of a rebuttal phase; the August-to-October window.
How do I install Wsdm Review Process in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill wsdm-review-process -a claude-code`. Or copy the skill folder (WSDM-Skills/skills/wsdm-review-process in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/wsdm-review-process in your project. Claude Code loads it when a task matches its description.
How do I install Wsdm Review Process in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill wsdm-review-process -a codex`. Or copy the skill folder (WSDM-Skills/skills/wsdm-review-process in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/wsdm-review-process in your project. Codex loads it when a task matches its description.
Can I use Wsdm 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 wsdm-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/wsdm-review-process, .gemini/skills/wsdm-review-process, .github/skills/wsdm-review-process and .opencode/skills/wsdm-review-process in your project.
What does Wsdm Review Process need to run?
SKILL.md names no scripts, command-line tools or credentials: Wsdm Review Process is instructions for the agent only.
Does Wsdm 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 Wsdm 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 Wsdm Review Process use?
Wsdm 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 Wsdm Review Process use?
About 1.7k tokens (SKILL.md is roughly 6.8k 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 Wsdm Review Process?
Skills that share tags, products or a category with Wsdm Review Process: Decide (alirezarezvani/claude-skills, 28k stars), Papers Skill (sickn33/agentic-awesome-skills, 47k stars), Deepseek Reason (ruvnet/ruflo, 74k stars) and Read arXiv Paper (karpathy/nanochat, 59k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Wsdm 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.