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 happyhappy-jun/writing-driven-autoresearch --skill hello-ralphthon-icmlgit clone --depth 1 https://github.com/happyhappy-jun/writing-driven-autoresearchWrote 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/happyhappy-jun/writing-driven-autoresearch/hello-ralphthon-icml)<a href="https://agentmods.dev/skills/happyhappy-jun/writing-driven-autoresearch/hello-ralphthon-icml"><img src="https://agentmods.dev/badge/skills/happyhappy-jun/writing-driven-autoresearch/hello-ralphthon-icml/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/happyhappy-jun/writing-driven-autoresearch/hello-ralphthon-icml"><img src="https://agentmods.dev/badge/skills/happyhappy-jun/writing-driven-autoresearch/hello-ralphthon-icml.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 | $0.00097 | $0.00789 |
| Opus 5 | $0.00048 | $0.00394 |
| Sonnet 5 | $0.00019 | $0.00158 |
| Haiku 4.5 | $0.00010 | $0.00079 |
Grade A, and why
hello-ralphthon-icml 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 11d 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hello Ralphthon @ICML
Use this skill to produce a concise welcome and orientation pack for Ralphthon @ICML: attendee-facing copy, operator briefing, QR/POP text, and next-step prompts that move people from arrival into the Ralph Loop.
Preflight
- Open the public Luma page at
https://luma.com/hjuo7aucwhen browsing is available and verify the visible title, venue, host, schedule, and check-in guidance. - If live verification is unavailable, say that the pack uses the embedded public facts below and identify attendee-visible facts that still need confirmation.
- Use public event facts and planning-safe summaries only. Never quote raw Fireflies, Slack, Telegram, email, guest exports, private notes, or participant/reviewer records.
- Keep world-model research separate from unverified sponsor or award claims.
Event Facts
- Title:
Ralphthon @ICML "Auto Research" supported by Codex - Luma:
https://luma.com/hjuo7auc - Venue:
NAVER D2SF 강남, 서울 서초구 서초대로74길 14 삼성화재 서초타워 18층 - Host/calendar: Team Attention / Goobong Jeong
- Strategic arc: hello and onboarding first, then auto-research, then world-model ideation.
Operating Context
- Treat QR, POP, webpage access, and guestbook prompts as engagement surfaces.
- Frame the hackathon around coding-agent efficiency and practical research acceleration.
- Use summarized planning context only; do not expose raw meeting transcripts or private notes.
- When possible, verify the live Luma page before finalizing public copy.
Workflow
- Draft a short attendee welcome.
- Add arrival, check-in, venue, and first-action orientation bullets.
- Produce short, medium, and operator-facing QR/POP variants with a clear action such as scan, check in, open the event page, or leave a guestbook note.
- Add an operator checklist and natural next prompts for the
auto-researchandworld-model-ideationskills. - Prefer compact, event-floor usable copy over long explanation.
Verification
- Recheck the public title, venue, schedule, and check-in guidance against the live Luma page when possible.
- Confirm every QR/POP variant has a clear call to action.
- Confirm the pack contains no private transcript, messaging, participant, reviewer, or operations data.
- Remove unverified sponsor, special-award, or world-model relationship claims.
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.
- 11d ago First seen · 64 lines · 97 tokens per session scan A 5de27caddd02
hello-ralphthon-icml is a skill published in the GitHub repository happyhappy-jun/writing-driven-autoresearch (21 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 97 tokens to every session and 789 once invoked, about $0.0005 per session on Opus 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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