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 guruvamsi-policharla/paper-review-skill --skill paper-reviewgit clone --depth 1 https://github.com/guruvamsi-policharla/paper-review-skillWrote 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/guruvamsi-policharla/paper-review-skill/paper-review)<a href="https://agentmods.dev/skills/guruvamsi-policharla/paper-review-skill/paper-review"><img src="https://agentmods.dev/badge/skills/guruvamsi-policharla/paper-review-skill/paper-review/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/guruvamsi-policharla/paper-review-skill/paper-review"><img src="https://agentmods.dev/badge/skills/guruvamsi-policharla/paper-review-skill/paper-review.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 | $0.00031 | $0.02886 |
| Opus 5 | $0.00015 | $0.01443 |
| Sonnet 5 | $0.00006 | $0.00577 |
| Haiku 4.5 | $0.00003 | $0.00289 |
Grade A, and why
paper-review 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 12d 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 — 470 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper Review Skill
You are a meticulous academic paper reviewer specializing in computer science research papers. Your task is to systematically review a LaTeX paper for correctness, clarity, and consistency.
Overview
This skill orchestrates a comprehensive paper review through:
- Discovery: Parse LaTeX structure to identify all sections
- Overview Building: Extract high-level understanding from introduction/overview sections
- Parallel Review: Dispatch sub-agents to review individual sections with shared context
- Report Generation: Aggregate findings into a structured
report.md
Phase 1: LaTeX Discovery
Step 1.1: Find the Main Document
Locate the main LaTeX file by searching for files containing \documentclass:
Search for: \documentclass
In files: *.tex
If multiple matches exist, prefer:
main.texpaper.tex- File with the shortest path
- Ask user if ambiguous
Step 1.2: Resolve All Includes
Parse the main document and recursively resolve all \input{} and \include{} commands:
Pattern matching:
\input{filename} → filename.tex (if no extension)
\input{filename.tex} → filename.tex
\include{filename} → filename.tex (if no extension)
Important considerations:
- Paths may be relative to the main file's directory
- Some projects use
\input{sections/intro}style paths - Handle both with and without
.texextension - Skip commented-out includes (lines starting with
%)
Build a complete file manifest:
main.tex
├── abstract.tex (if included)
├── sections/introduction.tex
├── sections/related.tex
├── sections/methods.tex
├── sections/results.tex
├── sections/conclusion.tex
└── appendix.tex (if included)
Step 1.3: Extract Section Structure
Parse all resolved files to build the section hierarchy:
Section commands to detect:
\section{Title}
\section*{Title}
\subsection{Title}
\subsection*{Title}
\subsubsection{Title}
\paragraph{Title}
For each section, record:
- Name: The section title
- Level: section (1), subsection (2), subsubsection (3), paragraph (4)
- File: Source file containing this section
- Line: Starting line number
- Content: All text until the next section of equal or higher level
What ships with it
2 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.
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.
- 12d ago First seen · 470 lines · 31 tokens per session scan A 67d226e85a0f
paper-review is a skill published in the GitHub repository guruvamsi-policharla/paper-review-skill (17 stars, last pushed 7mo ago), licensed MIT. It adds 31 tokens to every session and 2,886 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.
Other skills, from other repositories
design-taste-frontend
Anti-slop frontend skill for landing pages, portfolios, and redesigns. The agent reads the brief, infers the right design direction, and ships interfaces that do not look templated. Real design systems when applicable, audit-first on redesigns, strict pre-flight check.
image-to-code
Elite website image-to-code skill for Codex. For visually important web tasks, it must first generate the design image(s) itself, deeply analyze them, then implement the website to match them as closely as possible. In Codex, it must prefer large, readable, section-specific images instead of tiny compressed boards…
brandkit
Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional…
redesign-existing-projects
Upgrades existing websites and apps to premium quality. Audits current design, identifies generic AI patterns, and applies high-end design standards without breaking functionality. Works with any CSS framework or vanilla CSS.
gpt-taste
Elite UX/UI & Advanced GSAP Motion Engineer. Enforces Python-driven true randomization for layout variance, strict AIDA page structure, wide editorial typography (bans 6-line wraps), gapless bento grids, strict GSAP ScrollTriggers (pinning, stacking, scrubbing), inline micro-images, and massive section spacing.
minimalist-ui
Clean editorial-style interfaces. Warm monochrome palette, typographic contrast, flat bento grids, muted pastels. No gradients, no heavy shadows.