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Agent skill

Uai Related Work

by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills

A skill your agent uses when positioning a UAI submission within the probabilistic reasoning, graphical-model, causality, and Bayesian ML literature, covering PMLR archival status of recent UAI…

MITAuto-check passedResearch & Science

Install Uai Related Work

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

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

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills uai-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/UAI-Skills/skills/uai-related-work .claude/skills/uai-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
uai-related-work
GitHub stars
1.2k
Token cost
~1.7k tokens
SKILL.md length
778 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when positioning a UAI submission within the probabilistic reasoning, graphical-model, causality, and Bayesian ML literature, covering PMLR archival status of recent UAI…

  • Works in 5 steps: Sweep the last three UAI volumes' tables… → Repeat on the last two AISTATS volumes… → For each candidate neighbor, read the… → …
  • Positioning a UAI submission within the probabilistic reasoning
  • SKILL.md covers The lanes a UAI reviewer…, Establish the delta, not the…, Verifying venue attribution and Anonymity mechanics for prior…, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Uai Related Work is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when positioning a UAI submission within the probabilistic reasoning, graphical-model, causality, and Bayesian ML literature, covering PMLR archival status of recent UAI volumes, double-blind self-citation discipline, concurrent arXiv and workshop versions, and the cross-community citation coverage UAI reviewers check first.

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.

It sits in Research & Science, covering Literature review, Citation management and Academic paper search. It works with arXiv. 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 a UAI submission within the probabilistic reasoning
  • Graphical-model
  • Bayesian ML literature
  • Covering PMLR archival status of recent UAI volumes

Example prompts

  • “/uai-related-work”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Sweep the last three UAI volumes' tables of contents (v216, v244, v286 as of this
  2. Repeat on the last two AISTATS volumes and, for causal work, CLeaR; these pools
  3. For each candidate neighbor, read the assumption section before the method
  4. Trace forward citations of your three closest works for the concurrent-preprint
  5. Log every neighbor with a one-line delta at collection time. Deltas written during

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 (its code samples are bibtex).

    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

Uai Related Work loads about 1.7k tokens when it runs. Until then it costs about 87 tokens; SKILL.md has 778 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~87
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

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). 778 words, ~1,709 tokens.

Download SKILL.mdSave it as .claude/skills/uai-related-work/SKILL.md (or your agent's skills folder).
name
uai-related-work
description
Use when positioning a UAI submission within the probabilistic reasoning, graphical-model, causality, and Bayesian ML literature, covering PMLR archival status of recent UAI volumes, double-blind self-citation discipline, concurrent arXiv and workshop versions, and the cross-community citation coverage UAI reviewers check first.

Use this to audit positioning before submission. UAI sits at a junction of communities — ML conferences, statistics, causal inference, and the older probabilistic-AI tradition — and its reviewers typically belong to at least two of them. Related-work failures here are usually coverage failures: the paper positions against one community and gets reviewed by another.

The lanes a UAI reviewer expects covered

LaneWhere that literature livesThe question the reviewer asks
Prior UAI workPMLR volumes (v161 2021, v180 2022, v216 2023, v244 2024, v286 2025) and earlier AUAI-era proceedings"Do they know this venue already treated this problem?"
Sibling ML conferencesAISTATS, NeurIPS, ICML, ICLR"Is the nearest recent method compared or distinguished?"
Statistics literatureJASA, Biometrika, Annals of Statistics, JMLR"Is there a classical estimator or test that already does this?"
Causality communityUAI itself, CLeaR, epidemiology and econometrics journals"Which identification tradition does this extend — Pearl's graphical or the potential-outcomes one?"
FoundationsDecision theory, belief functions, imprecise probability"If the paper generalizes Bayes, is the relevant non-Bayesian line acknowledged?"

A causal-discovery submission citing only deep-learning-era papers, or a Bayesian-deep- learning submission ignoring the statistics literature on calibration, triggers the "backing" and "novelty" criteria simultaneously.

Establish the delta, not the bibliography

  • For the three closest works, state the technical difference in one sentence each: different assumption set, different identification regime, different complexity, different guarantee type. "Unlike [7], we do not require faithfulness" beats a paragraph of summary.
  • If the closest work appeared in the last two UAI or AISTATS cycles, compare empirically or explain concretely why comparison is impossible — silence on a same-venue neighbor is the most predictable review objection.
  • When your contribution weakens an assumption, show what the prior method does when that assumption fails; that experiment converts a related-work sentence into evidence.

Verifying venue attribution

Misattributed citations are common in this corner of ML because UAI, AISTATS, and ICML all publish through PMLR. Before submission, verify each PMLR citation against its volume page — the volume, not the paper title, determines the venue. Example of a correctly attributed UAI entry (metadata verified on the PMLR v161 sources):

bibtex
@inproceedings{ruiz21a,
  title     = {Unbiased gradient estimation for variational auto-encoders
               using coupled {M}arkov chains},
  author    = {Ruiz, Francisco J. R. and Titsias, Michalis K. and
               Cemgil, Taylan and Doucet, Arnaud},
  booktitle = {Proceedings of the Thirty-Seventh Conference on Uncertainty
               in Artificial Intelligence},
  series    = {Proceedings of Machine Learning Research},
  volume    = {161},
  pages     = {707--717},
  year      = {2021},
  publisher = {PMLR}
}

Older UAI papers (pre-PMLR era) live in AUAI Press proceedings; cite them as such rather than inventing PMLR volumes for them.

Anonymity mechanics for prior versions

  • Cite your own published prior work in the third person, exactly as you would cite a stranger's; omitting it entirely is worse, since reviewers who find it will suspect concealment.
  • The 2026 instructions forbade links that could reveal identity — so no linking your own arXiv page or repository from the related-work section.
  • Workshop versions and arXiv preprints: UAI's dual-submission concern is other archival venues; non-archival workshop exposure and preprints are traditionally tolerated at ML conferences, but the current CFP's own wording controls (2026 fine print: 待核实 before relying on it).
  • Concurrent submissions of the same work to another archival conference violate the standard rule; overlapping-but-distinct papers should be disclosed to chairs if the form asks.
Show full SKILL.md (285 more words)Show less

A search protocol that finds the embarrassing neighbor

The reviewer most likely to sink a UAI submission is the one who wrote the adjacent paper you missed. Search deliberately:

  1. Sweep the last three UAI volumes' tables of contents (v216, v244, v286 as of this pack's check) for your problem's keywords — titles at this venue are unusually literal, which makes the sweep fast.
  2. Repeat on the last two AISTATS volumes and, for causal work, CLeaR; these pools share reviewers with UAI.
  3. For each candidate neighbor, read the assumption section before the method section; adjacency at UAI is measured in assumptions, not architectures.
  4. Trace forward citations of your three closest works for the concurrent-preprint layer; note preprints separately since their claims are unrefereed.
  5. Log every neighbor with a one-line delta at collection time. Deltas written during the deadline sprint degenerate into "differs in setting".

Deltas that count here, deltas that do not

Positioning language calibrated to this reviewer pool:

  • Counts: weaker assumption set, broader graph class, finite-sample instead of asymptotic, exact instead of approximate (or a quantified approximation), lower complexity with the same guarantee, a guarantee where none existed.
  • Counts conditionally: better empirical calibration/coverage — if measured on the ladder of regimes, not one benchmark.
  • Does not count: "more scalable" without a complexity or wall-clock statement, "more flexible" without a named class the prior work excludes, "first deep-learning approach to X" when the classical approach is unbeaten.

If honest positioning shows the contribution is really about representation learning with incidental uncertainty, or pure learning theory with no probabilistic-reasoning core, the related-work audit has just made a venue recommendation — hand off to uai-topic-selection before polishing citations.

Output format

text
[Lane coverage] <covered lanes / missing lanes from the table>
[Closest three] <work → one-sentence technical delta>
[Same-venue neighbors] <recent UAI/AISTATS papers compared or explained>
[Attribution check] PMLR volumes verified? AUAI-era citations correct?
[Anonymity] self-citations third-person? no identifying links?

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

Open the folder on GitHubat commit 932eb23

Compare with similar skills

Uai 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.

Uai Related Work compared with similar skills
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Uai Related Work this skillbrycewang-stanford/Awesome-Journal-Skills1.2k—~1.7kAutomated safety check: PassMIT
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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
Arxiv MCP Serverblazickjp/arxiv-mcp-server3.2k—~353Automated safety check: PassApache-2.0

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Works with

Categories

Questions about Uai Related Work

What does Uai Related Work do?

A skill your agent uses when positioning a UAI submission within the probabilistic reasoning, graphical-model, causality, and Bayesian ML literature, covering PMLR archival status of recent UAI…. Uai Related Work is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when positioning a UAI submission within the probabilistic reasoning, graphical-model, causality, and Bayesian ML literature, covering PMLR archival status of recent UAI volumes, double-blind self-citation discipline, concurrent arXiv and workshop versions, and the cross-community citation coverage UAI reviewers check first.

When should I use Uai Related Work?

Uai Related Work fits situations like: positioning a UAI submission within the probabilistic reasoning; graphical-model; bayesian ML literature; covering PMLR archival status of recent UAI volumes.

How do I install Uai Related Work in Claude Code?

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

How do I install Uai Related Work in Codex?

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

Can I use Uai 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 uai-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/uai-related-work, .gemini/skills/uai-related-work, .github/skills/uai-related-work and .opencode/skills/uai-related-work in your project.

What does Uai Related Work need to run?

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

Does Uai 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 Uai 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 Uai Related Work use?

Uai 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 Uai Related Work use?

About 1.7k tokens (SKILL.md is roughly 6.8k 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 Uai Related Work?

Skills that share tags, products or a category with Uai Related Work: Literature Review (neflibata-feng/MyArxiv-Agent, 126 stars), Systematic Literature Review Builder (bytedance/deer-flow, 84k stars), Paper Research on arXiv (XiaomiMiMo/MiMo-Code, 14k stars) and Literature Review Agent (Ar9av/PaperOrchestra, 679 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Uai 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.