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 ssrajadh/paperview --skill gengit clone --depth 1 https://github.com/ssrajadh/paperviewWrote 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/ssrajadh/paperview/gen)<a href="https://agentmods.dev/skills/ssrajadh/paperview/gen"><img src="https://agentmods.dev/badge/skills/ssrajadh/paperview/gen.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 | $0.00057 | $0.04352 |
| Opus 5 | $0.00028 | $0.02176 |
| Sonnet 5 | $0.00011 | $0.00870 |
| Haiku 4.5 | $0.00006 | $0.00435 |
Grade A, and why
gen scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -fsSL "https://arxiv.org/pdf/$ARXIV" -o "$WORK/paper.pdf" # arXiv serves the PDF here How it starts
The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/ppv:gen — paper or codebase → narrated explainer video
The user's full request is: $ARGUMENTS
You are the planner/composer. You parse the request, read the source (a research paper or a
codebase), author a scene plan, and drive the deterministic ppv CLI (parse → TTS → render).
The CLI does the mechanical work; your job is the script and the visual choices.
ppv lives at ~/.paperview/venv/bin/ppv. Pre-flight: if that binary doesn't exist, the
toolchain isn't installed — tell the user to run /ppv:setup first, then stop. Don't attempt to
parse / tts / render without it (you'll just get No such file or directory).
1. Parse the request, then echo it back
From $ARGUMENTS extract: the source — a PDF (a local path, or an arXiv id / URL like
2310.06825 or arxiv.org/abs/2310.06825, which is downloaded for you — see §3), a
text/Markdown file, or a codebase (a local repo/directory, a set of source files, a
remote git URL like https://github.com/owner/repo, or a "explain project X" topic) — resolve
~, relative paths; if missing or ambiguous, ask — don't guess. A codebase takes a different path through
the steps below (no ppv parse, no figures — see §3). Then any steering:
- length / duration — a target time (e.g. "2 minutes", "~5 min") → target scene count at ~1 scene per 12–15s (default 10–12 scenes ≈ 3 min) and a per-scene narration word budget (~2.5 words/sec, so a 14s scene ≈ 35 words). Size narration to hit the target; TTS finalizes it.
- depth / audience — intro / general vs expert, intuition-heavy vs math-heavy. This sets
the narration register and the component mix: a general-audience cut leans on
statement/bullets/figureand explains terms; an expert cut spends more onequation/comparisonand assumes vocabulary. Keep claims calibrated either way (§4). For papers/repos with an algorithm or key source snippet, usecode— paste a real, focused snippet (~6-16 lines), setlang, and usehighlightLinesso the narration can walk through specific lines. - focus — a sub-topic to emphasize (spend more scenes there, trim the rest).
- aspect (
16:9default /9:16/1:1), provider/voice (default Kokoro, voiceaf_heart; runppv tts --list-voicesfor the voices each provider offers), captions (on/off — burned-in subtitles, default off; setmeta.captionsor pass--captions).
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 · 224 lines · 57 tokens per session scan A b0f98621437d
gen is a skill published in the GitHub repository ssrajadh/paperview (9 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 57 tokens to every session and 4,352 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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