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 atc-experimentsgit 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/atc-experiments)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/atc-experiments"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/atc-experiments/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/atc-experiments"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/atc-experiments.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 | $0.00074 | $0.01177 |
| Opus 5.5 | $0.00030 | $0.00471 |
| Sonnet 5.5 | $0.00015 | $0.00235 |
| Haiku 4.5 | $0.00007 | $0.00118 |
Grade A, and why
atc-experiments 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ATC Experiments
Match the evidence to the claim. ATC is the systems community's implementation-and-measurement venue: reviewers read for measured behavior on a real system, not asymptotics or accuracy on a dataset. In round two, 3-4 reviewers close to your subarea will open the artifact and probe whether the numbers are end-to-end, fair, and honest about cost. Design the evaluation so their first three objections are already answered.
Match evidence to claim shape
| If your claim is... | The evidence ATC expects |
|---|---|
| "Faster / lower latency" | End-to-end latency including tails (p99/p999) and throughput at a matched operating point, on a described testbed |
| "Lower overhead / cheaper" | The resource cost (CPU, memory, writes, energy) measured, at matched function — not just the headline win |
| "Scales" | Measurements across a real range of load/nodes/cores with the scaling curve and where it bends |
| "More reliable / correct" | Fault-injection or crash/recovery experiments, not just steady-state runs |
| "Useful in practice" (experience) | Production-derived workloads and lessons; what broke and what generalizes |
Real testbeds and workloads
- Describe the testbed so results are reproducible: CPU/NIC/SSD models, core counts, memory, kernel/OS versions, network topology, and any co-location. A result without its testbed is not a systems result.
- Use realistic workloads. Production-derived traces, standard benchmarks, or documented generators beat hand-picked inputs. State how the workload was obtained and why it is representative; if it is synthetic, justify the parameters.
- Warm-up and steady state. Say how you handled cold start, warm-up windows, and measurement duration — systems reviewers know where transient effects hide.
Fair baselines
- Compare against the strongest reasonable alternative, configured well (a strawman baseline is caught immediately). If you tuned your system, tune the baseline.
- Compare at a matched cost or operating point: same memory budget, same flash-write budget, same load. An unmatched comparison is the classic systems-reviewer objection.
- If no baseline exists, say so and use the unmodified system or an ablation of your own design as the reference.
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 · 95 lines · 74 tokens per session scan A 92e5504f159f
atc-experiments is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,264 stars, last pushed 19d ago), licensed MIT. It adds 74 tokens to every session and 1,177 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.
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