aaai-artifact-evaluati…
Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without…
Use when building the open-science and reproducibility story for an ASE (IEEE/ACM Automated Software Engineering) submission, covering the mandatory Data Availability Statement, anonymized-but-runnable tools, tool and subject-system provenance pinning, cached LLM outputs, and
$ npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill ase-reproducibility --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/ase-reproducibilityContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when building the open-science and reproducibility story for an ASE (IEEE/ACM Automated Software Engineering) submission, covering the mandatory Data Availability Statement, anonymized-but-runnable tools, tool and subject-system provenance pinning, cached LLM outputs, and
name: ase-reproducibility description: Use when building the open-science and reproducibility story for an ASE (IEEE/ACM Automated Software Engineering) submission, covering the mandatory Data Availability Statement, anonymized-but-runnable tools, tool and subject-system provenance pinning, cached LLM outputs, and staging for the ACM Available/Reusable artifact badges.
Build the reproducibility story at data-collection time, not at submission. ASE requires a **mandatory Data Availability Statement** in the paper and expects an **anonymized, runnable** artifact at review time; automated-SE artifacts are usually *tools*, so "runnable" means a reviewer can actually execute the automation on stated subjects. What is not pinned when you collect it cannot be reconstructed later.
appendix space).
**where it will live** after acceptance (an archival DOI target).
not a neutral placeholder.
than a modest, honest one.
author metadata, and any path revealing your identity (`/home/<you>/`, institutional URLs).
can execute the automation without your machine.
commit — automated-SE tools rot fast against moving toolchains.
For the tool:
experiments (including seeds for randomized components).
For subject systems and datasets:
criteria; and any manual **labeling protocol** with inter-rater agreement.
For LLM-based components:
artifact reproduces rather than calls a live, drifting API.
| Failure | Consequence | Prevention | |---|---|---| | Tool needs your exact machine | Reviewers cannot run it; artifact fails | Container/lockfile + minimal run path | | Subjects unpinned (branch, not SHA) | Numbers cannot be reproduced | Record SHAs + extraction date at collection | | LLM outputs uncached | Re-runs drift; comparison invalid | Cache outputs; record model IDs/dates | | Data Availability outside the 10 pages | Policy violation | Place it after Conclusions, inside the budget | | Identity leak in artifact | Anonymity violation | Scrub owner/metadata; re-host anonymized |
The submission-time artifact and the post-acceptance badge artifact are the *same package* matured. ASE offers **Artifacts Available** and **Artifacts Reusable** badges (ACM scheme); staging for them now avoids a scramble later (see `ase-artifact-evaluation`):
open license.
beyond reproducing your tables.
[Data Availability] present, after Conclusions, inside 10pp? matches the archive? [Tool] commit pinned, deps versioned, container/lockfile, minimal run path? [Subjects/data] SHAs + extraction date + selection/labeling protocol recorded? [LLM] model IDs/dates, prompts, cached outputs? [Anonymity] owner/metadata scrubbed; anonymized re-host? [Badge readiness] Available (DOI+license) / Reusable (docs+run path) staged?
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Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance,…
Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance,…
Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human…
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