Arize Evaluator
github/awesome-copilot
Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and…
A skill your agent uses when reasoning about how an ACM CoNEXT submission is evaluated, covering double-anonymous review, the two-round TPC process with online discussion and a TPC meeting, the…
MITAuto-check passed
Install Conext Review Process
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill conext-review-process -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills conext-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/CoNEXT-Skills/skills/conext-review-process .claude/skills/conext-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 "conext-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CoNEXT-Skills/skills/conext-review-process into .claude/skills/conext-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conext-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/CoNEXT-Skills/skills/conext-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 conext-review-process -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills conext-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/CoNEXT-Skills/skills/conext-review-process .agents/skills/conext-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 "conext-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CoNEXT-Skills/skills/conext-review-process into .agents/skills/conext-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conext-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 conext-review-process -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills conext-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/CoNEXT-Skills/skills/conext-review-process .cursor/skills/conext-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 "conext-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CoNEXT-Skills/skills/conext-review-process into .cursor/skills/conext-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conext-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 CoNEXT-Skills/skills/conext-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 conext-review-process -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills conext-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/CoNEXT-Skills/skills/conext-review-process .gemini/skills/conext-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 "conext-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CoNEXT-Skills/skills/conext-review-process into .gemini/skills/conext-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conext-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 conext-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 conext-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/CoNEXT-Skills/skills/conext-review-process .github/skills/conext-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 "conext-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CoNEXT-Skills/skills/conext-review-process into .github/skills/conext-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conext-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 conext-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 conext-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/CoNEXT-Skills/skills/conext-review-process .opencode/skills/conext-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 "conext-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/CoNEXT-Skills/skills/conext-review-process into .opencode/skills/conext-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conext-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
conext-review-process- GitHub stars
- 1.2k
- Token cost
- ~1.7k tokens
- SKILL.md length
- 770 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 an ACM CoNEXT submission is evaluated, covering double-anonymous review, the two-round TPC process with online discussion and a TPC meeting, the…
- Reasoning about how an ACM CoNEXT submission is evaluated
- SKILL.md covers Process model, Reading a decision against the…, How CoNEXT differs from its… and Who reads you, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Covering double-anonymous review
What it does
Conext Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when reasoning about how an ACM CoNEXT submission is evaluated, covering double-anonymous review, the two-round TPC process with online discussion and a TPC meeting, the Accept / Reject / one-shot "major" revision decision categories, the journal-style revise-and-resubmit re-read by the original reviewers, shepherding, and how CoNEXT's two-cycle process differs from SIGCOMM and NSDI.
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 an ACM CoNEXT submission is evaluated
- Covering double-anonymous review
- The two-round TPC process with online discussion and a TPC meeting
- The Accept / Reject / one-shot major revision decision categories
Example prompts
- “/conext-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
Conext Review Process loads about 1.7k tokens when it runs. Until then it costs about 103 tokens; SKILL.md has 770 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). 770 words, ~1,676 tokens.
Download SKILL.mdSave it as
.claude/skills/conext-review-process/SKILL.md (or your agent's skills folder).- name
- conext-review-process
- description
- Use when reasoning about how an ACM CoNEXT submission is evaluated, covering double-anonymous review, the two-round TPC process with online discussion and a TPC meeting, the Accept / Reject / one-shot "major" revision decision categories, the journal-style revise-and-resubmit re-read by the original reviewers, shepherding, and how CoNEXT's two-cycle process differs from SIGCOMM and NSDI.
CoNEXT Review Process
Model the pipeline before interpreting any single review. CoNEXT's process is journal-style: papers are PACMNET articles, and the one-shot "major" revision is a first-class decision, not a soft rejection. The most consequential mental shift for authors arriving from a plain accept/reject conference is that a major revision is a genuine revise-and-resubmit round re-read by the same reviewers — closer to a journal R&R — and that you get exactly one shot at it.
Process model
- Submission and review run on HotCRP with double-anonymity: authors and reviewers are mutually hidden through reviewing.
- Review proceeds in two rounds by TPC members, with online discussion and a TPC meeting; strong early-round papers advance, and clearly-below-bar papers may receive an early-reject notification partway through the cycle.
- First decisions fall into Accept, Reject, or a one-shot major revision. A major revision arrives with a summary of merits and a list of minimum necessary changes; authors get roughly two months to revise, and the same reviewers re-read the revision for a final accept/reject.
- Conditionally accepted or revised papers are typically shepherded by a designated TPC member who confirms the required changes were made before camera-ready.
- Accepted papers publish in PACMNET, scheduled to the closest issue, so final metadata, camera-ready compliance, and reproducibility follow-through matter as much as the initial verdict.
Reading a decision against the categories
| Decision | What it means | Author move |
|---|---|---|
| Accept | Contribution and evidence hold; minor polish only | Camera-ready + (optional) badge; do not reopen scope |
| One-shot major revision | Repairable gaps: a missing measurement, an unfair baseline, an unclear claim | Treat as a one-shot R&R: make or explicitly decline every "minimum necessary change," evidenced |
| Reject | Structural: wrong evaluation platform, no credible baseline, thin contribution | Reframe or reroute (SIGCOMM/NSDI/IMC/SIGMETRICS or the other cycle), do not lightly resubmit unchanged |
The strategic reading: write the initial submission so that whatever is weakest is fixable inside the revision window (a measurement you can add, a baseline you can tune) rather than structural (an evaluation platform you cannot rebuild in two months). The process rewards repairable papers, and because the revision is one shot, a half-addressed change list is what turns it into a rejection.
How CoNEXT differs from its siblings
- vs. SIGCOMM: SIGCOMM runs a single annual deadline and its own revision flavor; CoNEXT's identity is the two cycles a year feeding one program and the PACMNET journal framing. Never assume the two share a calendar, template, or revision mechanics.
- vs. NSDI: NSDI runs multiple deadlines with its own revision path too, but on the USENIX side with its own proceedings; CoNEXT's revision lands in a PACMNET issue. Do not carry NSDI's timing or format across.
- vs. IMC: IMC is measurement-focused and single-deadline; a CoNEXT measurement paper is judged alongside systems and architecture work in the same program, and can enter via either cycle.
Show full SKILL.md (304 more words)Show less
Who reads you
Expect a panel of networking TPC members matched to your subarea — systems, measurement, architecture, wireless. They look for evidence on the real target platform (a testbed, deployment, or trace, not a simulation standing in for hardware), check whether claims outrun the measurements, ask whether baselines are real and fairly tuned, and often open the artifact. Vague methodology gets caught in the two-round discussion, not skimmed.
Where author leverage actually exists
[Before submission] topic tags + cycle choice -> reviewer pool and calendar (largest lever)
[Round-1/early] factual corrections, targeted evidence, clarifying misreadings
[One-shot revision] the strongest lever: a tracked-change revision + point-by-point,
anonymous response letter re-read by the same reviewers, checked by a shepherd
[After reject] no appeal; reroute to a sibling venue or the other cycleA response moves borderline papers when it corrects a factual misreading or supplies a measurement a reviewer said was missing; it does not move papers when it argues taste. In a one-shot revision, silent omissions — a listed minimum-necessary change neither made nor explicitly declined with a reason — are what the second read punishes hardest.
Reading a review packet
Weight reviews before answering. A review that cites your section numbers, figures, and testbed setup was read closely and will be read closely again in the revision — its author is your likely advocate if the response holds. A review that discusses only novelty has left soundness and reproducibility to the others; answer each reviewer on the axis they raised. The major-revision change list is the scoring rubric for the second read: treat every item as mandatory unless you can justify declining it.
Misreadings to avoid
- Treating a major revision as a guaranteed accept — the second read is real and one-shot; budget the two-month window like a deadline.
- Treating the response as a debate — the TPC discussion and shepherd decide; your text is evidence for an advocate, not a closing argument.
- Assuming unanimity is required — a champion with answers to the other reviews can carry a paper through discussion.
- Projecting one cycle onto the other — the two cycles share a program but re-post their own dates; confirm the one you are in.
Output format
[Process stage] pre-submission / awaiting reviews / one-shot revision / final / accepted
[Cycle] December / June
[Decision category] accept / one-shot major revision / reject, with the criterion driving it
[Criterion map] each review point -> significance | soundness | measurement quality | baselines | clarity | reproducibility
[Leverage plan] the next-stage action that can actually change the outcome
[Forbidden moves] identity leak (incl. in the response letter) / unsupported new claims© 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 CoNEXT-Skills/skills/conext-review-process of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Conext 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 |
|---|---|---|---|---|---|---|
| Conext Review Process this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.7k | Automated safety check: Pass | MIT | |
| Arize Evaluatorgithub/awesome-copilot | 40k | 1 repos | ~8.1k | Automated safety check: Notes | MIT | |
| LLM Evaluationdavila7/claude-code-templates | 33k | 12 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Agent Evaluationsickn33/agentic-awesome-skills | 47k | 1 repos | ~2k | Automated safety check: Pass | MIT | |
| Deepseek Reasonruvnet/ruflo | 74k | — | ~626 | Automated safety check: Notes | MIT | |
| EvaluatorsArize-ai/phoenix | 12k | — | ~1.7k | Automated safety check: Pass | Custom licence |
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Questions about Conext Review Process
What does Conext Review Process do?
A skill your agent uses when reasoning about how an ACM CoNEXT submission is evaluated, covering double-anonymous review, the two-round TPC process with online discussion and a TPC meeting, the…. Conext Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when reasoning about how an ACM CoNEXT submission is evaluated, covering double-anonymous review, the two-round TPC process with online discussion and a TPC meeting, the Accept / Reject / one-shot "major" revision decision categories, the journal-style revise-and-resubmit re-read by the original reviewers, shepherding, and how CoNEXT's two-cycle process differs from SIGCOMM and NSDI.
When should I use Conext Review Process?
Conext Review Process fits situations like: reasoning about how an ACM CoNEXT submission is evaluated; covering double-anonymous review; the two-round TPC process with online discussion and a TPC meeting; the Accept / Reject / one-shot major revision decision categories.
How do I install Conext Review Process in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill conext-review-process -a claude-code`. Or copy the skill folder (CoNEXT-Skills/skills/conext-review-process in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/conext-review-process in your project. Claude Code loads it when a task matches its description.
How do I install Conext Review Process in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill conext-review-process -a codex`. Or copy the skill folder (CoNEXT-Skills/skills/conext-review-process in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/conext-review-process in your project. Codex loads it when a task matches its description.
Can I use Conext 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 conext-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/conext-review-process, .gemini/skills/conext-review-process, .github/skills/conext-review-process and .opencode/skills/conext-review-process in your project.
What does Conext Review Process need to run?
SKILL.md names no scripts, command-line tools or credentials: Conext Review Process is instructions for the agent only.
Does Conext 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 Conext 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 Conext Review Process use?
Conext 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 Conext Review Process use?
About 1.7k tokens (SKILL.md is roughly 6.7k 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 Conext Review Process?
Skills that share tags, products or a category with Conext Review Process: Arize Evaluator (github/awesome-copilot, 40k stars), LLM Evaluation (davila7/claude-code-templates, 33k stars), Agent Evaluation (sickn33/agentic-awesome-skills, 47k stars) and Deepseek Reason (ruvnet/ruflo, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Conext 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.