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-topic-selectiongit 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-topic-selection)<a href="https://agentmods.dev/skills/brycewang-stanford/awesome-journal-skills/ccs-topic-selection"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/ccs-topic-selection/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-topic-selection"><img src="https://agentmods.dev/badge/skills/brycewang-stanford/awesome-journal-skills/ccs-topic-selection.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 | $0.00056 | $0.00821 |
| Opus 5.5 | $0.00022 | $0.00328 |
| Sonnet 5.5 | $0.00011 | $0.00164 |
| Haiku 4.5 | $0.00006 | $0.00082 |
Grade A, and why
ccs-topic-selection 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CCS Topic Selection
Use this before writing. ACM CCS is the SIGSAC flagship: it rewards work with a concrete attacker, a defensible threat model, and evidence that survives an adversarial program committee. Decide venue by community and contribution type, never by prestige ranking.
Fit test
- Prefer CCS when the contribution is a broad computer-security result — a new attack class, a defense with measured cost, an applied-cryptography protocol, a systems or web-security mechanism, or a measurement study — aimed at the cross-area SIGSAC community.
- Route to IEEE S&P (Oakland) when the work suits that PC's taste for foundational or systematization framing and the November cycle fits your calendar better.
- Route to USENIX Security when the contribution is artifact-heavy systems security whose evidence lives in a runnable tool and open benchmark.
- Route to NDSS when the core is network- and distributed-system security (protocols, DNS, routing, malware infrastructure).
- Route to PETS/PoPETs when privacy is the primary lens rather than one property among many.
- Route to CRYPTO/EUROCRYPT when the contribution is cryptographic theory whose proof, not its deployment, is the result.
Fit signal table
| Signal in the project | CCS reading |
|---|---|
| New attack with a clearly bounded adversary and demonstrated impact | Core fit — the house genre |
| Defense evaluated against adaptive attacks with deployment cost | Core fit |
| Applied crypto protocol with implementation and measured overhead | Core fit |
| Internet-scale or ecosystem measurement with validated sampling | Core fit |
| Pure cryptographic hardness proof, no system | CRYPTO/EUROCRYPT or a theory venue |
| Privacy-first metrics with no other security property | PETS/PoPETs |
Vignette: where a side-channel result goes
A project extracts keys from a deployed TLS library via a microarchitectural side channel, with a proof-of-concept exploit and a constant-time patch. CCS reading: strong fit — a concrete attacker, measured leakage, and a defense with overhead numbers is exactly the CCS arc. Strip the exploit and keep only an abstract leakage bound, and it drifts toward a crypto theory venue; expand the network-measurement of vulnerable hosts into the whole story, and NDSS becomes plausible; foreground only the privacy harm to users, and PETS fits better.
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 · 68 lines · 56 tokens per session scan A 5c95927a3cd9
ccs-topic-selection is a skill published in the GitHub repository brycewang-stanford/Awesome-Journal-Skills (1,320 stars, last pushed 1mo ago), licensed MIT. It adds 56 tokens to every session and 821 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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