Deepseek Reason
ruvnet/ruflo
Reasoning-mode completion against DeepSeek's deepseek-reasoner model (R1) via /v1/chat/completions.
A skill your agent uses when reasoning about how CVPR review actually works at 16,000-submission scale, covering the OpenReview pipeline and timeline, reviewer-duty enforcement and desk rejects, the…
MITAuto-check passed
Install Cvpr Review Process
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cvpr-review-process -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills cvpr-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/CVPR-Skills/skills/cvpr-review-process .claude/skills/cvpr-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 "cvpr-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CVPR-Skills/skills/cvpr-review-process into .claude/skills/cvpr-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cvpr-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/CVPR-Skills/skills/cvpr-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 cvpr-review-process -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills cvpr-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/CVPR-Skills/skills/cvpr-review-process .agents/skills/cvpr-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 "cvpr-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CVPR-Skills/skills/cvpr-review-process into .agents/skills/cvpr-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cvpr-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 cvpr-review-process -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills cvpr-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/CVPR-Skills/skills/cvpr-review-process .cursor/skills/cvpr-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 "cvpr-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CVPR-Skills/skills/cvpr-review-process into .cursor/skills/cvpr-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cvpr-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 CVPR-Skills/skills/cvpr-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 cvpr-review-process -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills cvpr-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/CVPR-Skills/skills/cvpr-review-process .gemini/skills/cvpr-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 "cvpr-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CVPR-Skills/skills/cvpr-review-process into .gemini/skills/cvpr-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cvpr-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 cvpr-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 cvpr-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/CVPR-Skills/skills/cvpr-review-process .github/skills/cvpr-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 "cvpr-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CVPR-Skills/skills/cvpr-review-process into .github/skills/cvpr-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cvpr-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 cvpr-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 cvpr-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/CVPR-Skills/skills/cvpr-review-process .opencode/skills/cvpr-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 "cvpr-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CVPR-Skills/skills/cvpr-review-process into .opencode/skills/cvpr-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cvpr-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
cvpr-review-process- GitHub stars
- 1.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 779 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 CVPR review actually works at 16,000-submission scale, covering the OpenReview pipeline and timeline, reviewer-duty enforcement and desk rejects, the…
- Reasoning about how CVPR review actually works at 16
- SKILL.md covers The machine, by the numbers, Timeline anatomy (2026 cycle), Enforcement culture: the… and What a CVPR review contains, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- 000-submission scale
What it does
Cvpr Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when reasoning about how CVPR review actually works at 16,000-submission scale, covering the OpenReview pipeline and timeline, reviewer-duty enforcement and desk rejects, the reviewer LLM ban, AC and discussion dynamics, oral/highlight/poster decision tiers, and calibrating expectations to a ~25% acceptance rate.
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.
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 CVPR review actually works at 16
- 000-submission scale
- Covering the OpenReview pipeline and timeline
- Reviewer-duty enforcement and desk rejects
Example prompts
- “/cvpr-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
Cvpr Review Process loads about 1.6k tokens when it runs. Until then it costs about 85 tokens; SKILL.md has 779 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). 779 words, ~1,649 tokens.
Download SKILL.mdSave it as
.claude/skills/cvpr-review-process/SKILL.md (or your agent's skills folder).- name
- cvpr-review-process
- description
- Use when reasoning about how CVPR review actually works at 16,000-submission scale, covering the OpenReview pipeline and timeline, reviewer-duty enforcement and desk rejects, the reviewer LLM ban, AC and discussion dynamics, oral/highlight/poster decision tiers, and calibrating expectations to a ~25% acceptance rate.
CVPR Review Process
Use this to model what happens to a CVPR paper between upload and decision, and where author leverage exists. Every mechanism below is the 2026 cycle as verified 2026-07-08; scale numbers come from official CVPR program announcements.
The machine, by the numbers
The 2026 cycle put 16,092 submissions through full review (withdrawals and desk rejects excluded from that count) and accepted 4,090 — 25.42%. Doing that required roughly doubling the reviewer pool to 25,149 reviewers across 97 countries, coordinated by 909 area chairs. Two consequences follow for authors:
- Your reviewers are statistically likely to include first-time CVPR reviewers (the pool doubled in one year; official training material exists for a reason). Write for a competent generalist in vision, not the five people in your subfield.
- No individual paper gets much AC deliberation time by default. Papers that make the AC's job easy — clear claims, clean rebuttal, consistent reviews — get the benefit of scarce attention.
Timeline anatomy (2026 cycle)
| Phase | 2026 dates | What authors can do |
|---|---|---|
| Profile/abstract registration | Nov 6, 2025 | Fix profiles, finalize author list |
| Paper + CRF deadline | Nov 13, 2025 | Submit; after this, nothing |
| Supplement deadline | Nov 20, 2025 | Upload depth material |
| Reviewing | Dec – Jan 12, 2026 | Serve your own reviewer duties well |
| Reviews released | Jan 22, 2026 | Read cold, then triage |
| Rebuttal | → Jan 29, 2026 | One page (see cvpr-author-response) |
| Reviewer–AC discussion | Jan 30 – Feb 5, 2026 | Nothing — your rebuttal speaks |
| Decisions | Feb 20, 2026 | Plan camera-ready or resubmission |
Enforcement culture: the distinctive part
CVPR's response to scale is to make authorship and reviewing one social contract, with teeth that surprised people in recent cycles:
- Enrollment: submitting authors are expected to review and are added to the pool unless exempted; complete OpenReview profiles are mandatory for everyone.
- The nuclear clause: papers authored by a reviewer who fails to deliver assigned reviews on time, or delivers highly irresponsible ones, can be desk-rejected — all of that person's submissions — at PC discretion. A coauthor's negligence in January can kill your November submission.
- Reviewer LLM ban: reviews and meta-reviews may not be written by LLMs (local or API), and sharing substantial paper content with an LLM is prohibited; grammar checkers and background research are the carve-outs. As an author, this means a suspiciously LLM-flavored review is reportable to the AC, not just annoying.
# Confidential-channel escalation, in order
1. Rebuttal PDF → factual corrections all reviewers see
2. Confidential comment to AC (where the form allows)
→ reviewer misconduct: LLM-written review, review of the wrong paper,
demonstrably unread paper. Cite evidence, stay unemotional.
3. Never → contacting reviewers or ACs outside OpenReview; that
is an integrity violation on YOUR side.What a CVPR review contains
The review form's exact fields shift by cycle (待核实 each year), but the durable skeleton a CVPR review argues through is: summary of the paper in the reviewer's own words (misreadings here predict everything downstream), claimed strengths, weaknesses with the score-driving one usually listed first, and a recommendation with confidence. Read your reviews against that skeleton: a wrong summary is rebuttal priority one, because every weakness derived from it inherits the error.
Show full SKILL.md (320 more words)Show less
Decision tiers
Acceptance is not binary. The 2026 program sorted acceptances into poster, highlight (program-flagged posters, 578 papers per program trackers), and oral (141 papers in four parallel tracks), plus 74 award candidates — treat those tier counts as reported, and the tiering itself as the durable pattern. Tier decisions ride on review scores plus AC/SAC advocacy, which is one more reason the rebuttal's real audience is the AC.
After a rejection: mining reviews for signal
Roughly three of four reviewed papers exit here, so treat rejection processing as part of the process, not an aftermath:
- Separate objections into evidence gaps (missing baseline, unmatched backbone —
fix before any resubmission; CVF reviewer pools overlap and repeat objections
compound), communication failures (a reviewer missed something the paper does
say — a writing-style problem, see
cvpr-writing-style), and taste (novelty judgments that a different draw of three reviewers may not share). - Score patterns carry information: uniform lukewarm reviews usually mean a framing problem; one champion plus one detractor means the discussion phase decided it, and the rebuttal is where to look for what failed.
- Do not shop an unchanged paper to the next deadline. The overlap between CVPR, ICCV, and ECCV reviewer pools makes "same paper, new lottery ticket" a strategy with memory.
Calibration for authors
- A ~25% rate at 16k submissions means ~12,000 rejections of mostly competent papers. Rejection is the modal outcome for good work; plan the ICCV/ECCV/next-CVPR path at submission time, not in grief.
- Borderline papers live or die in discussion week. What moves them: a rebuttal that kills a factual objection, and one reviewer willing to champion. What doesn't: eloquence about importance.
- Reviews disagreeing 2-vs-1 is normal at this scale; the AC weighs arguments, not averages, more than authors assume.
Reverify each cycle
- Whether decisions remain single-round (no conditional-accept revision cycle existed in 2026).
- Reviewer-duty enforcement wording, LLM-policy scope, and review-form structure.
- Tier definitions (highlight/oral percentages shift with program capacity).
Output format
[Stage] pre-submission / in-review / rebuttal / discussion / decided
[Process risks] duty-compliance · profile validity · policy exposure
[Review read] per-reviewer: score-driver + fixability in one line
[AC theory] what the meta-reviewer needs in order to advocate
[Next actions] <dated, owner-assigned>© 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 CVPR-Skills/skills/cvpr-review-process of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Cvpr 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 |
|---|---|---|---|---|---|---|
| Cvpr Review Process this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Deepseek Reasonruvnet/ruflo | 74k | — | ~626 | Automated safety check: Notes | MIT | |
| Ejentum Reasoning Harnesssickn33/agentic-awesome-skills | 47k | 1 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Nowait Reasoning Optimizerdavila7/claude-code-templates | 32k | 2 repos | ~1.2k | Automated safety check: Pass | MIT | |
| ActualizeNeoLabHQ/context-engineering-kit | 1.7k | — | ~932 | Automated safety check: Pass | GPL-3.0 | |
| Recall Reasoningparcadei/Continuous-Claude-v3 | 3.9k | 1 repos | ~758 | Automated safety check: Pass | MIT |
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Questions about Cvpr Review Process
What does Cvpr Review Process do?
A skill your agent uses when reasoning about how CVPR review actually works at 16,000-submission scale, covering the OpenReview pipeline and timeline, reviewer-duty enforcement and desk rejects, the…. Cvpr Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when reasoning about how CVPR review actually works at 16,000-submission scale, covering the OpenReview pipeline and timeline, reviewer-duty enforcement and desk rejects, the reviewer LLM ban, AC and discussion dynamics, oral/highlight/poster decision tiers, and calibrating expectations to a ~25% acceptance rate.
When should I use Cvpr Review Process?
Cvpr Review Process fits situations like: reasoning about how CVPR review actually works at 16; 000-submission scale; covering the OpenReview pipeline and timeline; reviewer-duty enforcement and desk rejects.
How do I install Cvpr Review Process in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cvpr-review-process -a claude-code`. Or copy the skill folder (CVPR-Skills/skills/cvpr-review-process in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/cvpr-review-process in your project. Claude Code loads it when a task matches its description.
How do I install Cvpr Review Process in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cvpr-review-process -a codex`. Or copy the skill folder (CVPR-Skills/skills/cvpr-review-process in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/cvpr-review-process in your project. Codex loads it when a task matches its description.
Can I use Cvpr 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 cvpr-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/cvpr-review-process, .gemini/skills/cvpr-review-process, .github/skills/cvpr-review-process and .opencode/skills/cvpr-review-process in your project.
What does Cvpr Review Process need to run?
SKILL.md names no scripts, command-line tools or credentials: Cvpr Review Process is instructions for the agent only.
Does Cvpr 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 Cvpr 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 Cvpr Review Process use?
Cvpr 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 Cvpr Review Process use?
About 1.6k tokens (SKILL.md is roughly 6.6k 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 Cvpr Review Process?
Skills that share tags, products or a category with Cvpr Review Process: Deepseek Reason (ruvnet/ruflo, 74k stars), Ejentum Reasoning Harness (sickn33/agentic-awesome-skills, 47k stars), Nowait Reasoning Optimizer (davila7/claude-code-templates, 32k stars) and Actualize (NeoLabHQ/context-engineering-kit, 1.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Cvpr Review Process?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,228 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.