A skill your agent uses when positioning an ACM FAccT submission across its many disciplinary lanes — algorithmic fairness/ML, HCI, law and policy, STS and critical theory, and prior FAccT/FAT…

MITAuto-check passedResearch & Science

Install Facct Related Work

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill facct-related-work -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills facct-related-work --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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-related-work .claude/skills/facct-related-work && rm -rf skills-src

Use ~/.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/

Facts

Skill name
facct-related-work
GitHub stars
1.2k
Token cost
~1.4k tokens
SKILL.md length
589 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when positioning an ACM FAccT submission across its many disciplinary lanes — algorithmic fairness/ML, HCI, law and policy, STS and critical theory, and prior FAccT/FAT…

  • Positioning an ACM FAccT submission across its many disciplinary lanes — algorithmic fairness/ML
  • SKILL.md covers Positioning checks, FAccT literature lanes, Delta-first positioning vignette and Concurrent and prior-version…, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • STS and critical theory

What it does

Facct Related Work is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when positioning an ACM FAccT submission across its many disciplinary lanes — algorithmic fairness/ML, HCI, law and policy, STS and critical theory, and prior FAccT/FAT proceedings — writing delta-first contrast that a mixed reviewer pool will accept, citing borrowed constructs to their real origin, keeping self-citations mutually anonymous, and declaring overlap with workshops, preprints, and prior versions.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Literature review, Academic paper search and Positioning and messaging. 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

  • Positioning an ACM FAccT submission across its many disciplinary lanes — algorithmic fairness/ML
  • STS and critical theory
  • Prior FAccT/FAT proceedings — writing delta-first contrast that a mixed reviewer pool will accept
  • Citing borrowed constructs to their real origin

Example prompts

  • “/facct-related-work”

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 Related Work loads about 1.4k tokens when it runs. Until then it costs about 109 tokens; SKILL.md has 589 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~109
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

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). 589 words, ~1,420 tokens.

Download SKILL.mdSave it as .claude/skills/facct-related-work/SKILL.md (or your agent's skills folder).
name
facct-related-work
description
Use when positioning an ACM FAccT submission across its many disciplinary lanes — algorithmic fairness/ML, HCI, law and policy, STS and critical theory, and prior FAccT/FAT* proceedings — writing delta-first contrast that a mixed reviewer pool will accept, citing borrowed constructs to their real origin, keeping self-citations mutually anonymous, and declaring overlap with workshops, preprints, and prior versions.

Use this to audit novelty and disciplinary reach. FAccT reviewers come from different fields, and each expects to see the nearest work in their lane engaged. A fairness-metrics reviewer wants the ML fairness literature; a legal reviewer wants the relevant law and governance work; an STS/critical reviewer wants the theory you are (often implicitly) drawing on. The fastest way to lose a mixed panel is a bibliography that is deep in one field and blank in the others. Reopen the current CFP for anonymity, dual-submission, and prior-publication rules before advising.

Positioning checks

  • Name the FAccT novelty precisely. What is new: a fairness/transparency method, an empirical harm nobody had measured, an accountability framework, a reframing of a taken-for-granted construct, a qualitative account of an affected community, or a legal-technical synthesis?
  • Cover the disciplinary lanes (see table). A paper that cites only its home field reads as unaware of the interdisciplinary conversation FAccT exists to host.
  • Write delta-first. Each closely related work gets one sentence naming what it did and one naming what you do differently — across the divide where relevant ("the ML work optimized the metric; the legal work named the right; we connect them by...").
  • Cite borrowed constructs to their real origin. If you use "disparate impact," "contestability," "situated knowledge," or "the right to explanation," cite the field that coined it, not a second-hand ML paper — mixed reviewers notice mis-attribution instantly.
  • Preserve mutual anonymity. Cite your own prior work in the third person; never link reviewers to an identity-revealing preprint, repository, project page, or the arXiv version of this paper.
  • Declare overlap with a prior workshop/CRAFT version or concurrent submission; do not re-submit archival work as new.
Show full SKILL.md (309 more words)Show less

FAccT literature lanes

LaneTypical venues / bodiesWhat FAccT reviewers check
Algorithmic fairness & MLFAccT, NeurIPS/ICML/ICLR, JMLRWhether the nearest fairness measure/method is compared or distinguished
HCI & human factorsCHI, CSCWWhether prior work on how people use/contest the system is credited
Law, policy & governanceLaw reviews, policy journals, regulationWhether the relevant legal doctrine or regulatory instrument is engaged correctly
STS & critical theorySTS venues, critical data/algorithm studiesWhether the theoretical lineage of your critique is named, not just gestured at
Documentation & accountability infraPrior FAccT (datasheets, model cards, audits)Whether existing documentation/audit frameworks are built on rather than reinvented
Domain literature (health, credit, hiring...)The applied fieldWhether you understand the real decision context you study

A bibliography that reaches across at least the lanes your claim touches signals command of the interdisciplinary field; one confined to a single lane invites the "unaware of the neighbor discipline" critique that a mixed panel is unusually well-positioned to make.

Delta-first positioning vignette

Suppose the paper proposes a contestability mechanism for automated benefit decisions. Its neighbors span lanes: an ML paper on algorithmic recourse (technique, no institutional grounding), an HCI study of how claimants experience appeals (experience, no mechanism), and legal scholarship on due-process rights in automated administration (the right, no system). The novelty sentence names all three contrasts — a mechanism where recourse gave only a technique, grounded in the appeal experience HCI documented, realizing the due-process right the law names — which is exactly the cross-lane synthesis FAccT rewards.

Concurrent and prior-version judgment calls

text
[Concurrent arXiv work]   cite neutrally, state the difference, avoid unverifiable priority claims;
                          keep the citation mutually anonymous
[Your workshop/CRAFT version]  usually non-archival and citable, but confirm against the current CFP
                          and phrase so anonymity survives
[Prior short/position version] declare the overlap and state what the full paper adds beyond it
[Archival status unclear]  declare the overlap in the submission form rather than guessing

Eligibility red flags

  • Substantial text overlap with a published paper by the same authors (self-plagiarism risk).
  • A "new" audit that re-reports a prior dataset's disparities without a new question or population.
  • Citations confined to one discipline while the paper claims interdisciplinary contribution — the clearest signal that the interdisciplinarity is a label, not a method.

Output format

text
[Eligibility] clear / needs declaration / risky
[Lanes covered] <ML-fairness / HCI / law-policy / STS-critical / documentation / domain>
[Nearest 3 works] <work -> one-line cross-lane delta>
[Construct attribution] <borrowed term -> cited to its real origin? yes/no>
[Archival-overlap risk] <none / declare: what>
[Novelty sentence] <FAccT-ready contribution contrast across the relevant lanes>

© 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-related-work of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

Facct Related Work 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.

Facct Related Work compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Facct Related Work this skillbrycewang-stanford/Awesome-Journal-Skills1.2k—~1.4kAutomated safety check: PassMIT
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Preprint Search on bioRxivLigphiDonk/Oh-my--paper73912 repos~3.7kAutomated safety check: PassMIT
Systematic Literature Review Builderbytedance/deer-flow84k2 repos~4.3kAutomated safety check: PassMIT
Paper Research on arXivXiaomiMiMo/MiMo-Code14k—~1.5kAutomated safety check: PassMIT
Literature Review AgentAr9av/PaperOrchestra6791 repos~5.2kAutomated safety check: PassCustom licence

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Questions about Facct Related Work

What does Facct Related Work do?

A skill your agent uses when positioning an ACM FAccT submission across its many disciplinary lanes — algorithmic fairness/ML, HCI, law and policy, STS and critical theory, and prior FAccT/FAT…. Facct Related Work is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when positioning an ACM FAccT submission across its many disciplinary lanes — algorithmic fairness/ML, HCI, law and policy, STS and critical theory, and prior FAccT/FAT proceedings — writing delta-first contrast that a mixed reviewer pool will accept, citing borrowed constructs to their real origin, keeping self-citations mutually anonymous, and declaring overlap with workshops, preprints, and prior versions.

When should I use Facct Related Work?

Facct Related Work fits situations like: positioning an ACM FAccT submission across its many disciplinary lanes — algorithmic fairness/ML; STS and critical theory; prior FAccT/FAT proceedings — writing delta-first contrast that a mixed reviewer pool will accept; citing borrowed constructs to their real origin.

How do I install Facct Related Work in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill facct-related-work -a claude-code`. Or copy the skill folder (FAccT-Skills/skills/facct-related-work in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/facct-related-work in your project. Claude Code loads it when a task matches its description.

How do I install Facct Related Work in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill facct-related-work -a codex`. Or copy the skill folder (FAccT-Skills/skills/facct-related-work in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/facct-related-work in your project. Codex loads it when a task matches its description.

Can I use Facct Related Work 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-related-work -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-related-work, .gemini/skills/facct-related-work, .github/skills/facct-related-work and .opencode/skills/facct-related-work in your project.

What does Facct Related Work need to run?

SKILL.md names no scripts, command-line tools or credentials: Facct Related Work is instructions for the agent only.

Does Facct Related Work 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 Related Work 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 Related Work use?

Facct Related Work 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 Related Work use?

About 1.4k tokens (SKILL.md is roughly 5.7k 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 Facct Related Work?

Skills that share tags, products or a category with Facct Related Work: Literature Review (neflibata-feng/MyArxiv-Agent, 126 stars), Preprint Search on bioRxiv (LigphiDonk/Oh-my--paper, 739 stars), Systematic Literature Review Builder (bytedance/deer-flow, 84k stars) and Paper Research on arXiv (XiaomiMiMo/MiMo-Code, 14k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Facct Related Work?

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.