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 ccs-reproducibilitygit 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/ccs-reproducibility)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/ccs-reproducibility"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/ccs-reproducibility/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/ccs-reproducibility"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/ccs-reproducibility.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00058 | $0.00716 |
| Opus 5.5 | $0.00023 | $0.00286 |
| Sonnet 5.5 | $0.00012 | $0.00143 |
| Haiku 4.5 | $0.00006 | $0.00072 |
Grade A, and why
ccs-reproducibility 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CCS Reproducibility
Use this before submission and again before the artifact-evaluation deadline. Reopen the current CFP and call for artifacts to confirm what availability statement and packaging CCS expects this cycle.
Evidence map
- Map each security claim — every attack, defense guarantee, and measurement result — to a verifiable location: a script, a config, a dataset, a proof, or a logged run.
- For attacks, record the target's exact version and configuration, the attacker's resource budget, and the sequence of steps that reproduce the exploit.
- For defenses, record the workload, the overhead-measurement method, the hardware, and the adaptive attacker used, so the cost-versus-security tradeoff can be rechecked.
- For measurements, document the vantage point, the collection window, the sampling frame, known blind spots, and the ground-truth validation.
- When artifacts cannot be shared — licensing, responsible disclosure, subject safety, or premature-release risk — say so explicitly and offer partial, synthetic, or redacted artifacts that still let a reader assess the methodology.
Availability-posture table
| Claim type | What full sharing looks like | Honest fallback when sharing is blocked |
|---|---|---|
| Exploit against deployed software | Runnable PoC plus target build | Redacted PoC, disclosed-and-patched note, synthetic target |
| Defense with overhead numbers | Instrumented build and benchmark scripts | Binaries plus measurement scripts if source is proprietary |
| Internet-scale measurement | Dataset plus collection tooling | Aggregated data with subject-privacy justification for the rest |
| Cryptographic protocol | Reference implementation and test vectors | Spec plus test vectors if the implementation is embargoed |
Claiming an artifact is unavailable without a reason CCS accepts (a license, a disclosure embargo, subject safety) reads as evasion; state the specific reason and offer the closest shareable substitute.
Vignette: a measurement paper on vulnerable hosts
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 · 65 lines · 58 tokens per session scan A 8dad69ce0cc7
ccs-reproducibility is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,320 stars, last pushed 1mo ago), licensed MIT. It adds 58 tokens to every session and 716 once invoked, about $0.0002 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 2026-08-30.
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