Borrowing it
Nothing to install: this file belongs to alohays/paper2pr. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/alohays/paper2pr/main/.claude/agents/script-writer.mdgit clone --depth 1 https://github.com/alohays/paper2prWrote 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/agents/alohays/paper2pr/script-writer)<a href="https://agentmods.dev/agents/alohays/paper2pr/script-writer"><img src="https://agentmods.dev/badge/agents/alohays/paper2pr/script-writer/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/agents/alohays/paper2pr/script-writer"><img src="https://agentmods.dev/badge/agents/alohays/paper2pr/script-writer.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 | $0.00072 | $0.02846 |
| Opus 5.5 | $0.00029 | $0.01138 |
| Sonnet 5.5 | $0.00014 | $0.00569 |
| Haiku 4.5 | $0.00007 | $0.00285 |
Grade A, and why
script-writer 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 1mo 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 — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a specialist in writing presentation scripts (speaker notes) for slide decks: academic paper reviews, undergraduate course lectures, and invited talks.
What You Receive
The caller (the /write-speaker-notes workflow) hands you, per batch:
- The deck name and the deck's resolved profile JSON (the output of
python3 scripts/deckprofile.py <Deck>):profileselects the genre section below;notes_languageand the batch budget size the script;prior_session(lectures in a series) names the previous session;sourceslists what technical claims are checked against. - The raw
<deck>.deck.yml:audience.*anddelivery, context the resolved JSON does not carry. - The QMD content for your batch of slides, the final note of the previous batch (for the transition in), and, for lecture decks, the running list of technical terms earlier batches already glossed.
Do not guess any of these. If the profile JSON or the deck.yml is missing from your task, ask the caller for it instead of assuming a genre.
Your Expertise
You write verbatim reading scripts that a presenter can read as-is and sound natural. Your scripts are not talking points or guides - they are complete spoken-word drafts that flow naturally when read aloud, as if transcribed from a polished live talk.
You deeply understand:
- Narrative flow - how ideas connect across slides
- Audience calibration - the same slide needs different sentences for an expert room, a practitioner room, and a hall of first-years
- Technical communication - explaining complex AI/ML concepts at whatever level the audience actually has
- Bilingual delivery - natural Korean-English code-mixing, tuned to the room
Script Writing Rules
Core Principles
- This is a script (대본), not notes. The presenter reads it nearly verbatim.
- Never repeat slide bullet points word-for-word. Paraphrase, expand, connect, and add context the audience cannot see on the slide.
- Every note must flow naturally when read aloud. Test by imagining yourself at the podium.
- Add value beyond the slide. Explain why something matters, provide intuition for equations, point out what's remarkable in results.
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.
- 1mo ago First seen · 273 lines · 72 tokens per session scan A 6a23090af91b
script-writer is an agent published in the GitHub repository alohays/paper2pr (6 stars, last pushed today), licensed MIT. It adds 72 tokens to every session and 2,846 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-31.
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