Papers Skill
sickn33/agentic-awesome-skills
Skill for academic research workflows: search Semantic Scholar (200M+ papers), inspect citations, download arXiv PDFs, and extract PDF text.
Agent skill
Siggraph Review Process
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses to model the SIGGRAPH / SIGGRAPH Asia Technical Papers review pipeline and calibrate expectations, covering the single 6-point score scale, the primary/secondary/tertiary…
MITAuto-check passed
Install Siggraph Review Process
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill siggraph-review-process -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills siggraph-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/SIGGRAPH-Skills/skills/siggraph-review-process .claude/skills/siggraph-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 "siggraph-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGGRAPH-Skills/skills/siggraph-review-process into .claude/skills/siggraph-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "siggraph-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/SIGGRAPH-Skills/skills/siggraph-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 siggraph-review-process -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills siggraph-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/SIGGRAPH-Skills/skills/siggraph-review-process .agents/skills/siggraph-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 "siggraph-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGGRAPH-Skills/skills/siggraph-review-process into .agents/skills/siggraph-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "siggraph-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 siggraph-review-process -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills siggraph-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/SIGGRAPH-Skills/skills/siggraph-review-process .cursor/skills/siggraph-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 "siggraph-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGGRAPH-Skills/skills/siggraph-review-process into .cursor/skills/siggraph-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "siggraph-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 SIGGRAPH-Skills/skills/siggraph-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 siggraph-review-process -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills siggraph-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/SIGGRAPH-Skills/skills/siggraph-review-process .gemini/skills/siggraph-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 "siggraph-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGGRAPH-Skills/skills/siggraph-review-process into .gemini/skills/siggraph-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "siggraph-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 siggraph-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 siggraph-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/SIGGRAPH-Skills/skills/siggraph-review-process .github/skills/siggraph-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 "siggraph-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGGRAPH-Skills/skills/siggraph-review-process into .github/skills/siggraph-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "siggraph-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 siggraph-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 siggraph-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/SIGGRAPH-Skills/skills/siggraph-review-process .opencode/skills/siggraph-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 "siggraph-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/SIGGRAPH-Skills/skills/siggraph-review-process into .opencode/skills/siggraph-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "siggraph-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
siggraph-review-process- GitHub stars
- 1.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 545 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses to model the SIGGRAPH / SIGGRAPH Asia Technical Papers review pipeline and calibrate expectations, covering the single 6-point score scale, the primary/secondary/tertiary…
- Model the SIGGRAPH / SIGGRAPH Asia Technical Papers review pipeline and calibrate expectations
- SKILL.md covers The pipeline, One scale for everyone, Who reads your paper and Where leverage exists, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Covering the single 6-point score scale
What it does
Siggraph Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use to model the SIGGRAPH / SIGGRAPH Asia Technical Papers review pipeline and calibrate expectations, covering the single 6-point score scale, the primary/secondary/tertiary reviewer structure, the 1000-word rebuttal, the Technical Papers Committee meeting, conditional acceptance with second-stage verification, and the dual-track Journal-vs-Conference decision.
Its SKILL.md is about 1.3k 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
- Model the SIGGRAPH / SIGGRAPH Asia Technical Papers review pipeline and calibrate expectations
- Covering the single 6-point score scale
- The primary/secondary/tertiary reviewer structure
- The 1000-word rebuttal
Example prompts
- “/siggraph-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
Siggraph Review Process loads about 1.3k tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 545 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). 545 words, ~1,322 tokens.
Download SKILL.mdSave it as
.claude/skills/siggraph-review-process/SKILL.md (or your agent's skills folder).- name
- siggraph-review-process
- description
- Use to model the SIGGRAPH / SIGGRAPH Asia Technical Papers review pipeline and calibrate expectations, covering the single 6-point score scale, the primary/secondary/tertiary reviewer structure, the 1000-word rebuttal, the Technical Papers Committee meeting, conditional acceptance with second-stage verification, and the dual-track Journal-vs-Conference decision.
SIGGRAPH Review Process
Understanding the SIGGRAPH pipeline tells you where author leverage exists and where it does not.
The process is a hybrid: a conference clock (one deadline, a short rebuttal, a committee
meeting that decides in one round) wrapped around a journal outcome (an ACM Transactions on
Graphics article, with a conditional-accept revision to reach the journal bar). Facts below trace
to the SIGGRAPH 2026 reviewer-instructions/ethics page (resources/official-source-map.md);
reconfirm per cycle.
The pipeline
Submission form (authors locked) -> full submission (PDF + supplemental video)
-> assignment to a Technical Papers Committee member (primary) + secondary + external tertiary reviewers
-> reviews written; authors see the full set
-> rebuttal window (<=1000 words, text only)
-> Technical Papers Committee meeting: conditional accept / reject, and track assignment
-> [if conditional] second-stage review verifies the final version
-> publication in the SIGGRAPH issue of ACM TOG (or the Conference Proceedings)One scale for everyone
All submissions — dual-track and Journal-only — are scored on a single scale: Strong Reject, Reject, Borderline Reject, Borderline Accept, Accept, Strong Accept. There is no separate journal vs conference review; the same reviews serve both possible outcomes, and the committee decides the track afterward. Practically, this means you write one paper to the journal bar and let the committee route it — you do not get to argue "but it's only a conference paper."
Who reads your paper
- A primary (a Technical Papers Committee member) owns the paper, recruits reviewers, and presents it at the committee meeting.
- A secondary committee member and external tertiary reviewers provide additional expert reviews. Graphics reviewers are domain-deep and will run the supplemental video and scrutinize comparisons and timings.
- The rebuttal is read by these referees and folded into the committee discussion — the primary carries your paper's case into the room, so answer the objection the primary will have to defend.
Where leverage exists
| Stage | Author leverage | Reality |
|---|---|---|
| Submission | High | The paper + results video are 95% of the outcome; write and shoot them to the journal bar |
| Rebuttal | Narrow but real | 1000 text-only words can flip a factual error, rarely a judgment |
| Committee meeting | None directly | The primary argues on your behalf; you are not in the room |
| Conditional accept | High | Deliver every required change; the second-stage reviewer can still hold the paper |
| Track assignment | Low | The committee decides Journal vs Conference; you cannot appeal the track |
Show full SKILL.md (227 more words)Show less
Conditional acceptance and the second stage
A SIGGRAPH accept is almost always conditional: the committee lists required changes, and a
committee member verifies in a second reviewing process that the final version is acceptable
and the changes were made. This is the journal-grade revision folded into a conference calendar —
treat the conditions as binding, not advisory (see siggraph-author-response and
siggraph-camera-ready).
The dual-track decision
For a dual-track submission the committee chooses Journal (TOG) or Conference publication. Reviewers are less demanding about formal completeness, validation, and experimental evaluation when accepting to the Conference track — that track exists to publish riskier or earlier-stage work. A Conference-track accept is a real acceptance and a real SIGGRAPH presentation; it is published in the Conference Proceedings rather than the TOG issue. Do not read a Conference-track outcome as a rejection of the idea.
Calibrating outcomes
- SIGGRAPH acceptance has historically run in the ~20-30% range across the whole program with no fixed quota — the number emerges from the committee, not a target. (SIGGRAPH 2025: >970 submissions, 306 accepted; SIGGRAPH 2026: >1,120 submissions — exact 2026 accepts 待核实.)
- A borderline paper is decided by the video and the comparisons, not by the rebuttal. Invest accordingly before submission.
- If rejected, the standard path is to revise using the reviews and target the next cycle
(SIGGRAPH Asia after SIGGRAPH, or vice versa) — see
siggraph-workflowandsiggraph-topic-selection.
Output format
[Stage] pre-submission / awaiting reviews / rebuttal / post-decision / conditional
[Score read] where the pivotal reviewer sits on the 6-point scale
[Leverage] what this stage can and cannot change
[Rebuttal target] the factual error / specific question to address (if in window)
[If conditional] required changes -> plan -> second-stage risk
[Track expectation] dual-track (journal/conference) or journal-only© 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 SIGGRAPH-Skills/skills/siggraph-review-process of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Siggraph 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 |
|---|---|---|---|---|---|---|
| Siggraph Review Process this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Papers Skillsickn33/agentic-awesome-skills | 47k | 1 repos | ~2.1k | Automated safety check: Pass | 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 | |
| Bgpt Paper SearchK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~2k | Automated safety check: Pass | MIT | |
| Paper 2 Webdavila7/claude-code-templates | 32k | 12 repos | ~4k | Automated safety check: Notes | MIT |
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Questions about Siggraph Review Process
What does Siggraph Review Process do?
A skill your agent uses to model the SIGGRAPH / SIGGRAPH Asia Technical Papers review pipeline and calibrate expectations, covering the single 6-point score scale, the primary/secondary/tertiary…. Siggraph Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use to model the SIGGRAPH / SIGGRAPH Asia Technical Papers review pipeline and calibrate expectations, covering the single 6-point score scale, the primary/secondary/tertiary reviewer structure, the 1000-word rebuttal, the Technical Papers Committee meeting, conditional acceptance with second-stage verification, and the dual-track Journal-vs-Conference decision.
When should I use Siggraph Review Process?
Siggraph Review Process fits situations like: model the SIGGRAPH / SIGGRAPH Asia Technical Papers review pipeline and calibrate expectations; covering the single 6-point score scale; the primary/secondary/tertiary reviewer structure; the 1000-word rebuttal.
How do I install Siggraph Review Process in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill siggraph-review-process -a claude-code`. Or copy the skill folder (SIGGRAPH-Skills/skills/siggraph-review-process in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/siggraph-review-process in your project. Claude Code loads it when a task matches its description.
How do I install Siggraph Review Process in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill siggraph-review-process -a codex`. Or copy the skill folder (SIGGRAPH-Skills/skills/siggraph-review-process in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/siggraph-review-process in your project. Codex loads it when a task matches its description.
Can I use Siggraph 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 siggraph-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/siggraph-review-process, .gemini/skills/siggraph-review-process, .github/skills/siggraph-review-process and .opencode/skills/siggraph-review-process in your project.
What does Siggraph Review Process need to run?
SKILL.md names no scripts, command-line tools or credentials: Siggraph Review Process is instructions for the agent only.
Does Siggraph 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 Siggraph 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 Siggraph Review Process use?
Siggraph 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 Siggraph Review Process use?
About 1.3k tokens (SKILL.md is roughly 5.3k 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 Siggraph Review Process?
Skills that share tags, products or a category with Siggraph Review Process: Papers Skill (sickn33/agentic-awesome-skills, 47k stars), Read arXiv Paper (karpathy/nanochat, 59k stars), Hugging Face Paper Pages (huggingface/skills, 11k stars) and Bgpt Paper Search (K-Dense-AI/scientific-agent-skills, 48k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Siggraph 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.