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 agentmods add skills/nanoagentteam/research-claw/iclrnpx skills add nanoAgentTeam/research-claw --skill iclrgit clone --depth 1 https://github.com/nanoAgentTeam/research-clawWrote 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/nanoagentteam/research-claw/iclr)<a href="https://agentmods.dev/skills/nanoagentteam/research-claw/iclr"><img src="https://agentmods.dev/badge/skills/nanoagentteam/research-claw/iclr.svg" alt="Measured on agentmods" 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 | $0.00039 | $0.02809 |
| Opus 5 | $0.00019 | $0.01404 |
| Sonnet 5 | $0.00008 | $0.00562 |
| Haiku 4.5 | $0.00004 | $0.00281 |
Grade A, and why
iclr 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 6d 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 — 258 lines — stays where its author put it; the contents beside it link to each section on GitHub.
[SKILL: ICLR PAPER FORMAT]
Activate when: user mentions ICLR, International Conference on Learning Representations, or asks to use the ICLR template.
Execution Protocol
After this skill is activated, select the matching scenario based on user intent.
Shared Common Workflow
Before venue-specific template steps, also load and follow ml-paper-writing skill.
At minimum, apply these shared references:
writing-guide.md(narrative and clarity)citation-workflow.md(verified citations; no hallucinations)reviewer-guidelines.md(reviewer-facing quality checks)checklists.md(pre-submission gates)
Built-in template: templates/iclr2026/ (referred to as TEMPLATES_DIR below), targeting ICLR 2026.
Contents: iclr2026_conference.sty, iclr2026_conference.bst, iclr2026_conference.tex, iclr2026_conference.bib, math_commands.tex, fancyhdr.sty, natbib.sty.
Pre-step: Year Confirmation & Template Acquisition
This step MUST be completed before any scenario below.
- Confirm the target year with the user (default: latest available year).
- Check whether
TEMPLATES_DIRexists and includes required files:iclr2026_conference.sty,iclr2026_conference.bst,iclr2026_conference.tex,math_commands.tex,fancyhdr.sty,natbib.sty. - Use local built-in template only when BOTH conditions hold:
- target year = 2026
- files in
TEMPLATES_DIRare complete
- If either condition fails (target year is not 2026 OR local template files are missing/incomplete):
- Inform the user local built-in template is unavailable or year-mismatched.
- Guide the user to download the correct Author Kit from:
- Official website: https://iclr.cc → target year → "Author Guidelines" or "Submission Instructions"
- OpenReview: template link on the target-year submission page
- Overleaf fallback: search "ICLR [year] Conference Paper Template" on https://www.overleaf.com/latex/templates
- Unzip downloaded files directly into <PROJECT_CORE>.
- All subsequent steps must use the downloaded year-specific filenames (e.g.,
iclr2025_conference.sty).
- Filename substitution rule for all steps below:
- Treat
iclr2026_conferencein commands/examples as a placeholder for the resolved style basename from the selected.styfile. - Example: if the downloaded file is
iclr2025_conference.sty, replaceiclr2026_conferencewithiclr2025_conferenceeverywhere (\\usepackage,\\bibliographystyle, copy commands, checklist checks).
- Treat
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- templates/iclr2026/fancyhdr.sty 20 KB
- templates/iclr2026/iclr2026_conference.bib 629 B
- templates/iclr2026/iclr2026_conference.bst 26 KB
- templates/iclr2026/iclr2026_conference.pdf 196 KB
- templates/iclr2026/iclr2026_conference.sty 8.8 KB
- templates/iclr2026/iclr2026_conference.tex 17 KB
- templates/iclr2026/math_commands.tex 12 KB
- templates/iclr2026/natbib.sty 44 KB
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.
- 6d ago First seen · 258 lines · 39 tokens per session scan A 324abd162699
iclr is a skill published in the GitHub repository nanoAgentTeam/research-claw (292 stars, last pushed 2mo ago), licensed MIT. It adds 39 tokens to every session and 2,809 once invoked, about $0.0002 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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