Awesome Journal Skills is a collection of agent skill packs tailored to hundreds of academic journals across fields including economics, social science, medicine, science, and engineering. Researchers use the packs for tasks such as choosing topics, designing empirical strategies, preparing tables and figures, submitting papers, and responding to reviewers. The catalogue entries are the project's journal-specific skills and related plugins.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill asplos-artifact-evaluationgit clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/asplos-artifact-evaluation)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/asplos-artifact-evaluation"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/asplos-artifact-evaluation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/asplos-artifact-evaluation"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/asplos-artifact-evaluation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00069 | $0.01482 |
| Opus 5.5 | $0.00028 | $0.00593 |
| Sonnet 5.5 | $0.00014 | $0.00296 |
| Haiku 4.5 | $0.00007 | $0.00148 |
Grade A, and why
asplos-artifact-evaluation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ASPLOS Artifact Evaluation
Artifact evaluation at ASPLOS is a post-acceptance, opt-in, collaborative process: an independent committee works with authors to validate the paper's key results, and successful artifacts carry badges on the published paper (AE pages, checked 2026-07-08). It is also a tradition the venue itself highlights — systems readers increasingly treat an unbadged systems paper as a weaker citation. Treat AE as part of the publication, budgeted like a small sixth section.
The three badges and what each actually demands
| Badge | 2027 criterion (paraphrased from the AE pages) | Practical bar |
|---|---|---|
| Available | Artifact placed on a publicly accessible archival repository | A DOI-issuing archive (institutional or Zenodo-class); a GitHub URL alone is not archival |
| Functional | Evaluators can prepare and run the artifact; they document the steps they followed | Clean-machine install + a smoke experiment that completes in minutes, not hours |
| Reproducible | Evaluators validate the paper's key results | Per-claim run scripts whose output maps visibly onto specific figures/tables |
Evaluators assign scores per requested badge and record what they could and could not reproduce — so the artifact's job is to make their success path short and their failure modes diagnosable.
The Artifact Appendix is the contract
ASPLOS 2027 expects an Artifact Appendix built from the provided ae.tex template
(or equivalent sections) covering: all software, hardware, and dataset
dependencies; the key results to be reproduced; and how to prepare, run,
and validate the experiments. Write it as if the evaluator is competent, busy,
and using different hardware than yours:
- Dependencies include the awkward ones: kernel versions, privileged access, BIOS
settings, board models, expander firmware — everything from the state ledger in
asplos-reproducibility. - "Key results" means a selected subset: pick the claims that define the paper, not all 40 bars of every figure. Ambition here creates failure reports.
- Validation must be decidable: state the expected output and the tolerance within which the claim holds ("ordering preserved; absolute times ±15%").
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 129 lines · 69 tokens per session scan A c81decea5943
asplos-artifact-evaluation is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,372 stars, last pushed 1mo ago), licensed MIT. It adds 69 tokens to every session and 1,482 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-15.
asplos-artifact-evaluation compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| asplos-artifact-evaluationbrycewang-stanford/Awesome-Journal-Skills | Skill | 1.4k | 1mo ago | MIT | A | 69 | Claude Code |
| alterlab-pyhealthAlterLab-IEU/AlterLab-Academic-Skills | Skill | 85 | yesterday | MIT | A | 132 | Claude Code |
| alterlab-imaging-data-commonsAlterLab-IEU/AlterLab-Academic-Skills | Skill | 85 | yesterday | MIT | A | 90 | Claude Code |
| alterlab-datamolAlterLab-IEU/AlterLab-Academic-Skills | Skill | 85 | yesterday | MIT | A | 120 | Claude Code |
| alterlab-edaAlterLab-IEU/AlterLab-Academic-Skills | Skill | 85 | yesterday | MIT | A | 258 | Claude Code |
| alterlab-biorxivAlterLab-IEU/AlterLab-Academic-Skills | Skill | 85 | yesterday | MIT | A | 69 | Claude Code |
| alterlab-clinicaltrialsAlterLab-IEU/AlterLab-Academic-Skills | Skill | 85 | yesterday | MIT | A | 76 | Claude Code |