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/llv22/autoresearchwitheyes/paper-plannpx skills add llv22/AutoResearchWithEyes --skill paper-plangit clone --depth 1 https://github.com/llv22/AutoResearchWithEyesWrote 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/llv22/autoresearchwitheyes/paper-plan)<a href="https://agentmods.dev/skills/llv22/autoresearchwitheyes/paper-plan"><img src="https://agentmods.dev/badge/skills/llv22/autoresearchwitheyes/paper-plan.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 | $0.00047 | $0.02441 |
| Opus 5 | $0.00023 | $0.01221 |
| Sonnet 5 | $0.00009 | $0.00488 |
| Haiku 4.5 | $0.00005 | $0.00244 |
Grade A, and why
paper-plan 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 — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper Plan: From Review Conclusions to Paper Outline
Generate a structured, section-by-section paper outline from: $ARGUMENTS
Constants
All constants (REVIEWER_MODEL, VENUE, TEMPLATE_DIR) are defined in the project's CLAUDE.md. Read them from there before proceeding. Page limits are venue-dependent — see CLAUDE.md.
Inputs
The skill expects one or more of these in the project directory:
- NARRATIVE_REPORT.md or STORY.md — research narrative with claims and evidence
- GPT54_AUTO_REVIEW.md — auto-review loop conclusions
- Experiment results — JSON files in
figures/, screen logs, tables - IDEA_REPORT.md — from idea-discovery pipeline (if applicable)
If none exist, ask the user to describe the paper's contribution in 3-5 sentences.
Workflow
Step 1: Extract Claims and Evidence
Read all available narrative documents and extract:
- Core claims (3-5 main contributions)
- Evidence for each claim (which experiments, which metrics, which figures)
- Known weaknesses (from reviewer feedback)
- Suggested framing (from review conclusions)
Build a Claims-Evidence Matrix:
| Claim | Evidence | Status | Section |
|-------|----------|--------|---------|
| [claim 1] | [exp A, metric B] | Supported | §3.2 |
| [claim 2] | [exp C] | Partially supported | §4.1 |
Step 2: Determine Paper Type and Structure
Based on VENUE (from CLAUDE.md) and paper content, classify and select structure.
IMPORTANT: The section count is FLEXIBLE (5-8 sections). Choose what fits the content best. The templates below are starting points, not rigid constraints.
Empirical/Diagnostic paper:
1. Introduction (1.5 pages)
2. Related Work (1 page)
3. Method / Setup (1.5 pages)
4. Experiments (3 pages)
5. Analysis / Discussion (1 page)
6. Conclusion (0.5 pages)
Theory + Experiments paper:
1. Introduction (1.5 pages)
2. Related Work (1 page)
3. Preliminaries & Modeling (1.5 pages)
4. Experiments (1.5 pages)
5. Theory Part A (1.5 pages)
6. Theory Part B (1.5 pages)
7. Conclusion (0.5 pages)
— Total: 9 pages
Theory papers often need 7 sections (splitting theory into estimation + optimization, or setup + analysis). The total page budget MUST sum to the page limit for the target venue (see CLAUDE.md).
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 · 253 lines · 47 tokens per session scan A 3fe286e62da6
paper-plan is a skill published in the GitHub repository llv22/AutoResearchWithEyes (5 stars, last pushed 1mo ago), licensed MIT. It adds 47 tokens to every session and 2,441 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 2026-08-31.
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