/aistats-workflow
Use when planning an AISTATS project timeline from venue fit through abstract submission, full-paper upload, supplementary material, review release, author-reviewer discussion, decision, camera-ready, PMLR publication, registration, presentation, and artifact release, with
$ npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill aistats-workflow --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/aistats-workflow
Context preview
The summary Claude sees to decide when to auto-load this skill.
Use when planning an AISTATS project timeline from venue fit through abstract submission, full-paper upload, supplementary material, review release, author-reviewer discussion, decision, camera-ready, PMLR publication, registration, presentation, and artifact release, with
SKILL.md
aistats-workflow.SKILL.mdname: aistats-workflow
description: Use when planning an AISTATS project timeline from venue fit through abstract submission, full-paper upload, supplementary material, review release, author-reviewer discussion, decision, camera-ready, PMLR publication, registration, presentation, and artifact release, with backward-planning offsets for theory-plus-experiments papers.
AISTATS Workflow
Use this as the project-management skill for an AISTATS submission. Replace all dates with the current official timetable and work backwards from OpenReview cutoffs.
AISTATS is a conference, not a journal: it has no standing editor-in-chief and no article-processing charge. The rotating leadership is the per-edition General Chairs and Program Chairs (2026 General Chairs: Emtiyaz Khan and Yingzhen Li; Program Chairs: Arno Solin and Aaditya Ramdas, verified 2026-06-22), and the cost model is registration fees, not APCs — PMLR proceedings are open-access with no author fee. Conference organizers rotate yearly, so re-check the current CFP and organization page rather than carrying a name forward.
Milestones
- Venue fit: confirm the contribution is genuinely at the AI, ML, and statistics interface.
- Evidence lock: freeze theorem statements, assumptions, experiments, simulations,
baselines, reproducibility checklist, and supplement contents.
- Abstract deadline: submit real title, abstract, authors, subject areas, and conflicts.
- Full-paper deadline: upload anonymous PDF and required OpenReview fields.
- Supplement deadline: upload anonymized appendix/code/data if current cycle allows or
requires separate supplementary material.
- Review release: triage correctness, statistical validity, novelty, clarity, and
reproducibility concerns.
- Discussion period: draft concise anonymous text-only clarifications; avoid forbidden links
or unsupported new results.
- Decision: archive reviews, discussion, meta-review, decision, and submitted versions.
- Acceptance: prepare PMLR camera-ready files, registration, in-person presentation, and
public artifact release.
Backward plan from the paper deadline
| Weeks out (heuristic) | Theory-plus-experiments milestone | |---|---| | 8+ | Theorems proved, assumption set frozen | | 6 | Simulations designed against each theorem | | 4 | Real-data runs complete, seeds logged | | 3 | Full draft sitting in AISTATS two-column format | | 2 | Internal mock review by a statistics-minded reader | | 1 | Checklist pass, anonymity sweep, supplement assembly | | 0 | Abstract then full paper on OpenReview; supplement by its own cutoff |
These offsets are planning heuristics only — anchor every one of them to the current official timetable, never to a previous cycle's calendar.
Failure modes by stage
- Theory still moving at week 3 forces last-minute theorem edits nobody has verified — the
classic AISTATS correctness reject in the making.
- Leaving format conversion to the final week surfaces overflow late, because two-column math
is far tighter than a one-column working draft.
- Skipping the mock review forfeits the only chance to hear "your experiments violate
Assumption 2" from a friend instead of a reviewer.
- Building the supplement after the paper deadline under time pressure is how anonymity
leaks ship.
Coordination notes
- Assign one named owner for the reproducibility checklist and another for the anonymity
sweep; shared ownership is how both slip.
- Archive the exact submitted PDF, supplement, and checklist, since discussion-phase replies
must quote them precisely.
Output format
[Current stage] idea / experiments / writing / abstract / submission / supplement / discussion / accepted
[Next official deadline] <date and source, or unknown>
[Critical path] <three tasks that determine readiness>
[Risk register] <page/anonymity/statistical evidence/supplement/reproducibility/presentation>
[Owner map] <task -> person or role>
Read more
name: aistats-workflow description: Use when planning an AISTATS project timeline from venue fit through abstract submission, full-paper upload, supplementary material, review release, author-reviewer discussion, decision, camera-ready, PMLR publication, registration, presentation, and artifact release, with backward-planning offsets for theory-plus-experiments papers.
AISTATS Workflow
Use this as the project-management skill for an AISTATS submission. Replace all dates with the current official timetable and work backwards from OpenReview cutoffs.
AISTATS is a conference, not a journal: it has no standing editor-in-chief and no article-processing charge. The rotating leadership is the per-edition General Chairs and Program Chairs (2026 General Chairs: Emtiyaz Khan and Yingzhen Li; Program Chairs: Arno Solin and Aaditya Ramdas, verified 2026-06-22), and the cost model is registration fees, not APCs — PMLR proceedings are open-access with no author fee. Conference organizers rotate yearly, so re-check the current CFP and organization page rather than carrying a name forward.
Milestones
- Venue fit: confirm the contribution is genuinely at the AI, ML, and statistics interface.
- Evidence lock: freeze theorem statements, assumptions, experiments, simulations,
baselines, reproducibility checklist, and supplement contents.
- Abstract deadline: submit real title, abstract, authors, subject areas, and conflicts.
- Full-paper deadline: upload anonymous PDF and required OpenReview fields.
- Supplement deadline: upload anonymized appendix/code/data if current cycle allows or
requires separate supplementary material.
- Review release: triage correctness, statistical validity, novelty, clarity, and
reproducibility concerns.
- Discussion period: draft concise anonymous text-only clarifications; avoid forbidden links
or unsupported new results.
- Decision: archive reviews, discussion, meta-review, decision, and submitted versions.
- Acceptance: prepare PMLR camera-ready files, registration, in-person presentation, and
public artifact release.
Backward plan from the paper deadline
| Weeks out (heuristic) | Theory-plus-experiments milestone | |---|---| | 8+ | Theorems proved, assumption set frozen | | 6 | Simulations designed against each theorem | | 4 | Real-data runs complete, seeds logged | | 3 | Full draft sitting in AISTATS two-column format | | 2 | Internal mock review by a statistics-minded reader | | 1 | Checklist pass, anonymity sweep, supplement assembly | | 0 | Abstract then full paper on OpenReview; supplement by its own cutoff |
These offsets are planning heuristics only — anchor every one of them to the current official timetable, never to a previous cycle's calendar.
Failure modes by stage
- Theory still moving at week 3 forces last-minute theorem edits nobody has verified — the
classic AISTATS correctness reject in the making.
- Leaving format conversion to the final week surfaces overflow late, because two-column math
is far tighter than a one-column working draft.
- Skipping the mock review forfeits the only chance to hear "your experiments violate
Assumption 2" from a friend instead of a reviewer.
- Building the supplement after the paper deadline under time pressure is how anonymity
leaks ship.
Coordination notes
- Assign one named owner for the reproducibility checklist and another for the anonymity
sweep; shared ownership is how both slip.
- Archive the exact submitted PDF, supplement, and checklist, since discussion-phase replies
must quote them precisely.
Output format
[Current stage] idea / experiments / writing / abstract / submission / supplement / discussion / accepted [Next official deadline] <date and source, or unknown> [Critical path] <three tasks that determine readiness> [Risk register] <page/anonymity/statistical evidence/supplement/reproducibility/presentation> [Owner map] <task -> person or role>
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Open skill - /aaai-camera-ready
Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and
Open skill - /aaai-experiments
Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and
Open skill - /aaai-related-work
Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a
Open skill - /aaai-reproducibility
Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that
Open skill

