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 FAccT submission is evaluated — mutually-anonymous review by a mixed CS+law+social-science pool matched via author-selected focus areas, Area…
MITAuto-check passed
Install Facct Review Process
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill facct-review-process -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills facct-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/FAccT-Skills/skills/facct-review-process .claude/skills/facct-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 "facct-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/FAccT-Skills/skills/facct-review-process into .claude/skills/facct-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "facct-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/FAccT-Skills/skills/facct-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 facct-review-process -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills facct-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/FAccT-Skills/skills/facct-review-process .agents/skills/facct-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 "facct-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/FAccT-Skills/skills/facct-review-process into .agents/skills/facct-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "facct-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 facct-review-process -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills facct-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/FAccT-Skills/skills/facct-review-process .cursor/skills/facct-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 "facct-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/FAccT-Skills/skills/facct-review-process into .cursor/skills/facct-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "facct-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 FAccT-Skills/skills/facct-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 facct-review-process -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills facct-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/FAccT-Skills/skills/facct-review-process .gemini/skills/facct-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 "facct-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/FAccT-Skills/skills/facct-review-process into .gemini/skills/facct-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "facct-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 facct-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 facct-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/FAccT-Skills/skills/facct-review-process .github/skills/facct-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 "facct-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/FAccT-Skills/skills/facct-review-process into .github/skills/facct-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "facct-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 facct-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 facct-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/FAccT-Skills/skills/facct-review-process .opencode/skills/facct-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 "facct-review-process" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/FAccT-Skills/skills/facct-review-process into .opencode/skills/facct-review-process/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "facct-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
facct-review-process- GitHub stars
- 1.2k
- Token cost
- ~1.5k tokens
- SKILL.md length
- 674 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 FAccT submission is evaluated — mutually-anonymous review by a mixed CS+law+social-science pool matched via author-selected focus areas, Area…
- The short factual-correction rebuttal
- SKILL.md covers Process model, Reading a decision against the…, The interdisciplinary reviewer… and Where author leverage actually…, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- The new Accept/Revise/Reject decision with a revise-and-resubmit round
What it does
Facct Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when reasoning about how an ACM FAccT submission is evaluated — mutually-anonymous review by a mixed CS+law+social-science pool matched via author-selected focus areas, Area Chairs, the short factual-correction rebuttal, the new Accept/Revise/Reject decision with a revise-and-resubmit round, and how FAccT's interdisciplinary process differs from a pure-ML conference's single-shot rebuttal.
Its SKILL.md is about 1.5k 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
- The short factual-correction rebuttal
- The new Accept/Revise/Reject decision with a revise-and-resubmit round
- How FAccTs interdisciplinary process differs from a pure-ML conferences single-shot rebuttal
Example prompts
- “s interdisciplinary process differs from a pure-ML conference”
- “/facct-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
Facct Review Process loads about 1.5k tokens when it runs. Until then it costs about 104 tokens; SKILL.md has 674 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). 674 words, ~1,512 tokens.
Download SKILL.mdSave it as
.claude/skills/facct-review-process/SKILL.md (or your agent's skills folder).- name
- facct-review-process
- description
- Use when reasoning about how an ACM FAccT submission is evaluated — mutually-anonymous review by a mixed CS+law+social-science pool matched via author-selected focus areas, Area Chairs, the short factual-correction rebuttal, the new Accept/Revise/Reject decision with a revise-and-resubmit round, and how FAccT's interdisciplinary process differs from a pure-ML conference's single-shot rebuttal.
FAccT Review Process
Model the pipeline before interpreting any single review. FAccT's process has two features that surprise authors arriving from a pure-ML venue: the reviewer pool is interdisciplinary (a computer scientist, a lawyer, and a social scientist may all be assigned), and — new for the 2026 edition — the decision set is Accept / Revise / Reject, where Revise is a genuine revise-and-resubmit round, not a soft reject. Your paper is matched to reviewers and Area Chairs by the focus areas you selected at registration, so those choices shape who reads you as much as your title does.
Process model
- Submission and review run on OpenReview (new for 2026) with mutual anonymity: authors and reviewers are hidden from each other.
- Papers are matched to reviewers and Area Chairs by disciplinary focus area, so an interdisciplinary paper is typically read by people from more than one field — a strength and a risk (each expects their lane's rigor).
- Reviewers weigh relevance to the conference and the chosen area, and quality and clarity — correctness, depth of exposition (how well you contextualize approach, methodology, perspective, and domain), and an honest evaluation of both strengths and limitations.
- After preliminary reviews, a short rebuttal window lets authors correct factual errors and misunderstandings and signpost minor edits — it is not for re-arguing substantive disagreement.
- Area Chairs synthesize reviews into a recommendation: Accept, Revise, or Reject. Revise papers address AC-prioritized concerns by the revision deadline and are re-reviewed before a final decision.
- Accepted papers are archival ACM proceedings (or non-archival by author choice) and are presented in person.
Reading a decision against the categories
| Decision | What it means | Author move |
|---|---|---|
| Accept | Contribution and rigor hold; minor polish only | Camera-ready; do not reopen scope |
| Revise | Repairable gaps: a missing disaggregation, an under-argued harm, a construct concern, a thin cross-lane engagement | Treat as an R&R: address each AC-prioritized concern, evidenced, by the deadline |
| Reject | Structural: not FAccT-shaped, harm claim unsupported, one-discipline paper misrouted | Reframe or reroute (NeurIPS/ICML/CHI/AIES/law), do not lightly resubmit unchanged |
The strategic reading: write the initial submission so that whatever is weakest is fixable inside the revision window (an analysis you can add, a limitation you can bound, a construct you can validate) rather than structural (a study design or a venue-fit problem you cannot repair in weeks). The 2026 process is built to reward repairable papers.
Show full SKILL.md (287 more words)Show less
The interdisciplinary reviewer reality
Expect readers from different fields, matched by your focus areas. A fairness-methods reviewer checks your metrics, baselines, and disaggregation; a legal reviewer checks whether you use the doctrine correctly; a qualitative reviewer checks your coding, reflexivity, and treatment of participants. The common failure is a paper strong for one and naive to another — so answer each reviewer on the axis they raised, and do not dismiss a cross-lane objection as "not my field": at FAccT it is precisely the point.
Where author leverage actually exists
[Before submission] focus-area selection -> which disciplines review you (largest lever)
[Rebuttal] factual corrections and misreadings only; not a debate
[Revise round] the strongest lever: address each AC-prioritized concern with concrete changes,
re-read before the final decision
[After reject] no appeal; reroute to a sibling venue or the CRAFT track, or resubmit next cycleA rebuttal moves borderline papers when it fixes a factual misreading a reviewer built an objection on; it does not move papers when it argues taste. In the Revise round, an unaddressed AC-prioritized concern — neither fixed nor explicitly and reasonably declined — is what turns the re-review against you.
Reading a review packet
Weight reviews before answering. A review that engages your subgroup tables, your codebook, or the specific doctrine was read closely and will be read closely again — that reviewer is your likely advocate if the revision holds. A review from an adjacent discipline that raises a framing or harm concern is not noise; it is the interdisciplinary check the venue exists for, and the Area Chair will weight it.
Misreadings to avoid
- Treating Revise as a guaranteed accept — the re-review is real; budget the short window like a deadline.
- Treating the rebuttal as the revision — the rebuttal is for factual corrections; substantive fixes belong in the Revise round.
- Dismissing the out-of-field reviewer — the mixed panel is the design, not an accident.
- Projecting a pure-ML process — FAccT is not single-shot accept/reject; and the Revise round, OpenReview, and rebuttal specifics are 2026-new, so re-confirm them each cycle.
Output format
[Process stage] pre-submission / awaiting reviews / rebuttal / revise / final / accepted
[Decision category] accept / revise / reject, with the criterion driving it
[Criterion map] each review point -> relevance | correctness | depth | strengths-and-limits | discipline
[Leverage plan] the next-stage action that can actually change the outcome
[Forbidden moves] identity leak / arguing taste in rebuttal / ignoring the out-of-field reviewer© 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 FAccT-Skills/skills/facct-review-process of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Facct 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 |
|---|---|---|---|---|---|---|
| Facct Review Process this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.5k | Automated safety check: Pass | MIT | |
| Arize Evaluatorgithub/awesome-copilot | 40k | 1 repos | ~8.1k | Automated safety check: Notes | MIT | |
| LLM Evaluationdavila7/claude-code-templates | 32k | 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 Facct Review Process
What does Facct Review Process do?
A skill your agent uses when reasoning about how an ACM FAccT submission is evaluated — mutually-anonymous review by a mixed CS+law+social-science pool matched via author-selected focus areas, Area…. Facct Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when reasoning about how an ACM FAccT submission is evaluated — mutually-anonymous review by a mixed CS+law+social-science pool matched via author-selected focus areas, Area Chairs, the short factual-correction rebuttal, the new Accept/Revise/Reject decision with a revise-and-resubmit round, and how FAccT's interdisciplinary process differs from a pure-ML conference's single-shot rebuttal.
When should I use Facct Review Process?
Facct Review Process fits situations like: the short factual-correction rebuttal; the new Accept/Revise/Reject decision with a revise-and-resubmit round; how FAccTs interdisciplinary process differs from a pure-ML conferences single-shot rebuttal.
How do I install Facct Review Process in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill facct-review-process -a claude-code`. Or copy the skill folder (FAccT-Skills/skills/facct-review-process in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/facct-review-process in your project. Claude Code loads it when a task matches its description.
How do I install Facct Review Process in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill facct-review-process -a codex`. Or copy the skill folder (FAccT-Skills/skills/facct-review-process in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/facct-review-process in your project. Codex loads it when a task matches its description.
Can I use Facct 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 facct-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/facct-review-process, .gemini/skills/facct-review-process, .github/skills/facct-review-process and .opencode/skills/facct-review-process in your project.
What does Facct Review Process need to run?
SKILL.md names no scripts, command-line tools or credentials: Facct Review Process is instructions for the agent only.
Does Facct 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 Facct 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 Facct Review Process use?
Facct 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 Facct Review Process use?
About 1.5k tokens (SKILL.md is roughly 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 Facct Review Process?
Skills that share tags, products or a category with Facct Review Process: Arize Evaluator (github/awesome-copilot, 40k stars), LLM Evaluation (davila7/claude-code-templates, 32k 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 Facct 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.