paper-parser

A skill that reads an arXiv-style physics PDF, such as a research preprint or technical report, and produces a structured record of its equations, figures, captions, and numerical claims.

In plain words
What is it for?
Use it to extract LaTeX and SymPy equations, figure images and captions, quoted claims, and standardized units from one PDF.
Why use it?
It turns difficult scientific papers into organized data that later tools can use without manually rechecking every page.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/leventilo/mobius/paper-parser
Any agent
npx skills add leventilo/mobius --skill paper-parser
Clone the repo
git clone --depth 1 https://github.com/leventilo/mobius

Made for: Claude Code, Codex.

Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,952 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00068 $0.03952
Opus 5 $0.00034 $0.01976
Sonnet 5 $0.00014 $0.00790
Haiku 4.5 $0.00007 $0.00395

Measured 2d ago against content hash 0169a18e4271, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

paper-parser 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 2d ago.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/__init__.py, scripts/extract_claims.py, scripts/extract_equations.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/paper-parser/SKILL.md · 285 lines

How it starts

The opening of the file, as written. The whole thing — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.

paper-parser

1. Purpose and scope

paper-parser is the entry node of the Mobius DAG. It reads a single PDF (arXiv preprint, journal article, or technical report) and produces the paper sub-tree of the canonical SimSpec — equations as LaTeX and sympy, figures as PNGs with captions and sub-panel structure, and numerical claims with verbatim source quotes and UCUM-normalized units.

The skill does NOT:

  • reason about physics (that is physics-interpreter's job — governing equations get tagged here, classified there)
  • compose simulation specifications (that is simspec-author)
  • verify claims against simulation output (that is science-integrity / paper-diff)
  • generate visualizations (that is viz-mapper)
  • emit Python primitives or simulator code (that is primitive-generator)

Everything downstream of paper-parser assumes that the JSON returned here is correct, lossless within the limits documented below, and reproducible across re-runs given the same PDF bytes.

2. Input

Required:

  • pdf_path: str — absolute path to a readable PDF file. Multi-column arXiv layout is the assumed common case.

Optional:

  • page_range: tuple[int, int] | None — inclusive (start, end) page hint. Default scans the entire document. Useful when the orchestrator wants to skip references or supplementary material on a known-structured paper.
  • focus_sections: list[str] | None — section title hints (e.g. ["Methods", "Results"]). Treated as a soft prior on which pages matter for claim extraction; never used to drop pages outright.

The PDF is opened read-only. Nothing is written next to the input. All artefacts go to /tmp/mobius_figures/ and /tmp/mobius_parser_cache/.

3. Output

A JSON object matching the paper sub-tree of the SimSpec schema:

{
  "doi": "10.xxxx/...",
  "arxivId": "2501.12345",
  "title": "...",
  "authors": ["..."],
  "abstract": "...",
  "equations": [
    {
      "id": "eq-1",
      "latex": "\\nabla \\cdot \\vec{E} = \\rho/\\epsilon_0",
      "sympy_repr": "Eq(Derivative(E, x) + ..., rho/epsilon_0)",
      "variables": ["E", "rho", "epsilon_0"],
      "page": 3,
      "bbox": [120.5, 410.0, 480.2, 442.7],
      "surrounding_context": "...prose ±200 chars around the equation...",
      "confidence": "high"
    }
  ],
  "figures": [
    {
      "id": "fig-1",
      "png_path": "/tmp/mobius_figures/<sha256>/fig-1.png",
      "caption": "Verbatim caption text...",
      "subpanels": [
        {"label": "a", "bbox_in_figure": [0.0, 0.0, 0.5, 1.0], "png_path": "..."}
      ],
      "inline_numerical_claims": [
        {"value": 532.0, "unit": "nm", "location_hint": "panel (a) wavelength"}
      ],
      "page": 5,
      "confidence": 0.86
    }
  ],
  "numerical_claims": [
    {
      "id": "claim-1",
      "value": 1.4e-3,
      "unit_ucum": "kg.m-3",
      "value_uncertainty": 0.05e-3,
      "section": "Results",
      "source_quote": "the measured density was 1.4 x 10^-3 kg/m^3 +/- 0.05 x 10^-3",
      "claim_type": "measurement",
      "confidence": 0.92
    }
  ]
}

Read the full file on GitHub · 285 lines

Files

What ships with it

4 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.

Changes

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.

  1. 2d ago First seen · 285 lines · 68 tokens per session scan A 0169a18e4271

Subscribe to this mod's changes

paper-parser is a skill published in the GitHub repository leventilo/mobius (9 stars, last pushed 4mo ago), licensed MIT. It adds 68 tokens to every session and 3,952 once invoked, about $0.0003 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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