Analyze paper
Extract structured information from a research paper: system model, theorem statements, proof techniques, complexity claims, and red flags. Use when asked to analyze, summarize, or review an academic paper.From its SKILL.md
npx -y skills add SebastianElvis/reaper --skill analyze-paperAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 9 stars9 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its file declares
Copied from the file, not written here
The file declares its own license as Apache-2.0. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
5.6 KB, ~1.2k tokens by cl100k_base, as published. Nobody here has run it
Analyze Paper
Extract structured information from an academic paper, producing a comprehensive summary that downstream skills can build on.
Usage
Invoke this skill by name with the paper path (and optional flags). On slash-command hosts, prefix with / (e.g. /analyze-paper <args>).
# Analyze the primary paper under study
analyze-paper path/to/paper.pdf
# Analyze a literature paper with research goal as context
analyze-paper reaper-workspace/papers/2024-1234.pdf --goal "post-quantum threshold signatures" --output reaper-workspace/papers/2024-1234-notes.md
Argument parsing: The first non-flag argument is the paper path. Optional flags:
--output <path>: Write output to the given path instead of the defaultreaper-workspace/notes/paper-summary.md.--goal "<text>": The research goal as additional context. When provided, the output includes a Relevance section assessing how the paper relates to this goal, and reading depth is calibrated by relevance (see Step 1).
Instructions
1. Read the Paper
Read the paper at the provided path using your host's file-read primitive (works for PDFs and text files on hosts that support PDF reading; otherwise extract text first).
Follow the three-pass strategy from ../reaper/references/paper-analysis.md:
- Pass 1 (skeleton): Abstract, introduction, conclusion, theorem statements. Identify the main claims.
- Pass 2 (construction): Protocol details, proof sketches, figures. Understand the key technical idea.
- Pass 3 (proofs): Full formal proofs, appendices, security reductions. Verify logical steps.
When --goal is provided, calibrate depth by relevance to the goal: Pass 1 for all papers; Pass 2 for medium-relevance; all three passes for high-relevance papers.
2. Extract Information
For each section below, extract the relevant information. When extracting theorem statements or formal claims, copy them verbatim — do not paraphrase.
Critical: Distinguish what the paper claims (in the introduction, abstract) from what it actually proves (in the theorems, proofs). Note any discrepancies.
3. Write Output
Write the extracted information to reaper-workspace/notes/paper-summary.md (or the path specified by --output) with the following structure:
# Paper Summary: [Paper Title]
## Metadata
- **Title**:
- **Authors**:
- **Venue/Year**:
- **Paper ID**: (ePrint, arXiv, DOI)
- **Link**: (e.g., https://arxiv.org/abs/XXXX.XXXXX or https://eprint.iacr.org/YYYY/NNNN)
## Problem Statement
What problem does this paper solve? Why does it matter?
## System Model
[Extract all model dimensions relevant to the paper's domain. Consult `../reaper/references/model.md` for the domain-appropriate dimensions to extract. Every applicable dimension must have a concrete answer.]
## Construction Overview
High-level protocol description. Key technical idea. Building blocks used.
## Key Results
List each theorem/claim verbatim:
1. **Theorem X.X**: [exact statement]
- Model: [exact model under which this is proved]
- Proof technique: [game-based / simulation / reduction]
## Proof Technique
Overall proof approach. Key lemmas. Reduction chain. Where the corruption threshold and network model are used.
## Complexity Claims
- Communication:
- Rounds:
- Computation:
## Strengths
[Label each major/minor: novelty, methodology fit, proof rigor, evaluation quality, clarity.]
## Weaknesses
[Label each major/minor/fatal: broken methodology, missing proofs, unjustified claims, unfair comparisons, unclear writing, overclaimed results.]
## Key Definitions and Notation
Non-standard notation. Formal definitions referenced by the proofs.
## Red Flags
Any concerns identified during reading (see `../reaper/references/paper-analysis.md` for common red flags).
## Relevance
[Present ONLY when --goal is provided. Tag one or more: *problem definition*, *formalization*, *solution technique*, *negative result*, *literature/context*, *writing model*. One sentence per tag explaining how this paper relates to the research goal.]
Sections should be proportional to what the paper warrants. If a paper has no complexity claims, omit that section. If the proof technique is trivial, keep it brief. The template is a guide, not a form to fill in mechanically.
Quality Criteria
- Every theorem statement is copied verbatim, not paraphrased
- When a System Model section is present, it covers every dimension that applies to the paper (network, adversary, trust, communication, crypto). Omit the section only if the paper does not warrant it (e.g. pure information-theoretic results); never partially fill it
- Strengths and weaknesses are labeled with severity (major/minor/fatal) and are honest — if the paper looks solid, say so; if there are concerns, list them specifically
- Red flags section is honest — no concerns is a valid answer
- The summary is useful standalone — a reader who hasn't seen the paper should understand the key claims and approach
- When
--goalis provided, relevance tags are specific to the goal, not generic ("related to our topic") - If the PDF is unreadable, try page-by-page with the
pagesparameter. If it still fails, report the error — do not fabricate a summary
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.
Gives 0 of the 12 instructions most research analysis skills give in ~1.2k tokens
Counted across 1,213 of the 2,113 authors here whose files we hold, read 2026-09-06
- Cite sources for every important claimin 47 of 1213, across 38 files
- Separate facts from inferences and recommendationsin 21 of 1213, across 12 files
- Write findings to a markdown filein 19 of 1213
- Label every insight with a confidence levelin 18 of 1213, across 8 files
- Read product marketing context before asking questionsin 18 of 1213, across 8 files
- Rank themes by frequency and intensityin 16 of 1213, across 6 files
- Establish research mode before proceedingin 16 of 1213, across 6 files
- Segment survey responses by customer tier or tenurein 16 of 1213, across 6 files
- Categorize support tickets before analyzingin 16 of 1213, across 6 files
- Weight research sources from the last twelve monthsin 16 of 1213, across 6 files
- Use at least five data points per segmentin 15 of 1213, across 5 files
- Extract verbatim quotes for all research findingsin 15 of 1213, across 5 files
Said here and by no other author read
- Read the paper using the three-pass strategy
- Calibrate reading depth based on relevance to the goal
- Copy theorem statements and formal claims verbatim
- Distinguish paper claims from actual proofs
- Identify discrepancies between claims and proofs
- Extract all relevant system model dimensions
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.