paper-writing-bench skillA
paper-writing-bench is agent-read markdown (skill) from ar9av/paperorchestra: Reverse-engineer raw materials (Sparse idea, Dense idea, experimental log) from an existing AI research paper to build a benchmark case for evaluating paper-writing pipelines. Replicates the PaperWritingBench dataset construction procedure from arXiv:2604.05018 §3 / App. C. TRIGGER when the user asks to "build a benchmark case from this paper", "reverse-engineer raw materials", or "evaluate my pipeline against PaperWritingBench"..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# PaperWritingBench (§3) Faithful implementation of the PaperWritingBench dataset construction procedure from PaperOrchestra (Song et al., 2026, arXiv:2604.05018, §3 and App. C, F.2). The original benchmark contains 200 papers (100 CVPR 2025 + 100 ICLR 2025). For each paper, the authors reverse-engineer the (I, E) tuple by stripping narrative flow from the original PDF using the three prompts in App. F.2. You can use this skill to reverse-engineer your own benchmark cases from any paper PDF. ## What this skill does Given an existing AI research paper (PDF or markdown extract), produce: - `idea.md` (Sparse variant) — high-level concept note, no math, no experimental results - `idea.md` (Dense variant) — detailed technical proposal with LaTeX equations and variable definitions, but still no experimental results - `experimental_log.md` — exhaustive raw experimental setup, numeric data, and qualitative observations, with all narrative references stripped These three files form a complete (I, E) input pair for the paper-orchestra pipeline. You can then run the pipeline and compare its output to the original paper using `paper-autoraters`. ## Inputs …
Read the whole file at its exact version.
How to install
mdr add ar9av/paperorchestra/paper-writing-bench@git:20260409.c2de31bmdr add ar9av/paperorchestra/paper-writing-bench@sha256:c4f90aaae0ba10adPin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_k6ooqjd2opeujaza)
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Versions
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (5625 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
ar9av/paperorchestra · 664 stars · license NOASSERTION · pushed 2026-09-21 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_k6ooqjd2opeujaza GET https://markdownregistry.com/api/v1/resolve?ref=ar9av/paperorchestra/paper-writing-bench GET https://markdownregistry.com/api/v1/blob/c4f90aaae0ba10ad6a89bdccdd7d9e732c2fa03743f9d2976d258689c0e98ea8
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