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 claesbackman/AI-research-feedback --skill paper-versiongit clone --depth 1 https://github.com/claesbackman/AI-research-feedbackWrote 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/claesbackman/ai-research-feedback/paper-version)<a href="https://agentmods.dev/skills/claesbackman/ai-research-feedback/paper-version"><img src="https://agentmods.dev/badge/skills/claesbackman/ai-research-feedback/paper-version/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/claesbackman/ai-research-feedback/paper-version"><img src="https://agentmods.dev/badge/skills/claesbackman/ai-research-feedback/paper-version.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 | $0.00043 | $0.04239 |
| Opus 5 | $0.00022 | $0.02119 |
| Sonnet 5 | $0.00009 | $0.00848 |
| Haiku 4.5 | $0.00004 | $0.00424 |
Grade A, and why
paper-version 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 9d 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 — 277 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper Versions
Convert a LaTeX research paper project into an accessible audience-facing version, review it for accuracy, and produce a standalone HTML page.
Input
$ARGUMENTS[0]— Output format:brief,1page, or5page(required)
Format definitions
brief— A structured 2-page policy brief with fixed sections: The Question, What We Do, Key Findings, Policy Implications, Caveats. Formal but accessible. No jargon.1page— One flowing page of prose for a general audience. No section headers. Written like a short article. Leads with the main finding.5page— A five-page narrative summary with light structure (Background, What We Did, What We Found, Why It Matters, Limitations). Accessible to an educated non-specialist.
Instructions
Step 0 — Validate input
If $ARGUMENTS[0] is not one of brief, 1page, 5page, stop and tell the user: "Please specify a format: brief, 1page, or 5page."
Set FORMAT = the argument value.
Step 1 — Reader Agent
Launch an Agent (subagent_type: general-purpose) with this task:
You are reading a LaTeX research paper project. Your job is to extract the full content of the paper into a clean, structured plain-text representation that will be used by a writer agent.
Instructions:
- Find the main
.texfile in the current directory. It is usually the file that contains\documentclassor\begin{document}. Use Glob to search for**/*.texfiles, then identify the root file.- Read the root
.texfile. Wherever you find\input{...}or\include{...}commands, read those files too, recursively, until you have assembled the full paper text.- Strip LaTeX markup: remove commands like
\textbf{},\emph{},\cite{},\label{},\ref{},\footnote{}, equation environments, figure environments, table environments. Keep the text content. For tables, summarize the key numbers in prose form. For figures, note what the figure shows based on the caption.- Extract and clearly label these components:
- Title
- Authors
- Abstract (verbatim)
- Introduction (full text)
- Data/Empirical Setting (if present)
- Methods/Approach (condensed)
- Main Results — list every key quantitative finding, with exact numbers, units, and confidence intervals as stated in the paper. Be exhaustive here.
- Robustness/Heterogeneity (condensed)
- Conclusion
- Key claims made by the authors — list every causal or interpretive claim the authors make explicitly, noting the exact language they use (e.g., "we find that X causes Y" vs. "X is associated with Y")
- Extract figure information: scan the full
.texsource for\includegraphicscommands. For each one, record:
- The filename as specified (e.g.,
figures/fig1orfig_results)- The caption text from the nearest
\caption{}command- Which section of the paper the figure appears in List these under a Figures section in your output, formatted as:
FIGURE: [filename] | CAPTION: [caption text] | SECTION: [section name]- Identify the 1-2 figures that best illustrate the paper's main finding and mark them with
[KEY FIGURE].- Return the full extraction as structured markdown. Do not summarize or interpret — just extract.
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.
- 9d ago First seen · 277 lines · 43 tokens per session scan A 6b8963472bd7
paper-version is a skill published in the GitHub repository claesbackman/AI-research-feedback (477 stars, last pushed 12d ago), licensed MIT. It adds 43 tokens to every session and 4,239 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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