What is paper-workbench?

A research workflow for collecting, reading, comparing, and organizing academic papers and related sources.

Use it to skim or deeply read papers, compare studies, synthesize findings, identify research gaps, or build a literature-review outline from PDFs, DOIs, arXiv links, or existing workbench files.

It keeps basic paper information separate from deeper analysis, making literature work easier to reuse across projects.

paper-workbench — Skill for Claude Code by bahayonghang

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.

Any agent

npx skills add bahayonghang/my-ai-cli-toolkit --skill paper-workbench

Clone the repo

git clone --depth 1 https://github.com/bahayonghang/my-ai-cli-toolkit

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/bahayonghang/my-ai-cli-toolkit/paper-workbench/github.svg)](https://agentmods.dev/skills/bahayonghang/my-ai-cli-toolkit/paper-workbench)

Your own site

<a href="https://agentmods.dev/skills/bahayonghang/my-ai-cli-toolkit/paper-workbench"><img src="https://agentmods.dev/badge/skills/bahayonghang/my-ai-cli-toolkit/paper-workbench/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/bahayonghang/my-ai-cli-toolkit/paper-workbench"><img src="https://agentmods.dev/badge/skills/bahayonghang/my-ai-cli-toolkit/paper-workbench.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 102 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,806 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 2 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

high System Prompt Leakage · line 178
Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.

Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
high System Prompt Leakage · line 208
Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.

Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.

How audits are shown

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.

Model	Per session	Once invoked
Fable 5.1	$0.00102	$0.01806
Opus 5.5	$0.00041	$0.00722
Sonnet 5.5	$0.00020	$0.00361
Haiku 4.5	$0.00010	$0.00181

Measured 1mo ago against content hash 15aeb60a4f7d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

paper-workbench scanned grade A with 1 finding 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.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/normalize_paper.py, scripts/workbench_io.py, scripts/xray_io.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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

allowed-tools: Read, Write, WebFetch, Bash(curl *), Bash(python *), Bash(pytest *)

skills/research-learning-knowledge/paper-workbench/SKILL.md · 216 lines

How it starts

The opening of the file, as written. The whole thing — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Paper Workbench

Unified entrypoint for paper intake, strategic reading, multi-paper synthesis, and review construction.

Keep paper-record as the normalization layer. Do not merge high-level analysis back into the normalized record.

In the python commands below, <skill-dir> is this skill's base directory, announced when the skill loads. Substitute that literal path; it is not an environment variable. Bundled scripts self-locate, so only the path needs to resolve.

When to use

Use this skill when the job is to:

read one paper quickly
deeply deconstruct one paper
compare or synthesize multiple papers
build a review outline or gap map
normalize paper sources into reusable machine-readable artifacts

Do not use this skill when the primary job is to implement a paper from its methods into working code. That implementation work is out of scope for this skill.

Public interfaces

paper-record — normalized single-paper facts
researcher-profile — user research anchor
paper-deep-read — single-paper strategic analysis artifact
literature-synthesis — cross-paper integration artifact
review-outline — literature-review planning artifact

Accepted inputs

arXiv IDs and arXiv URLs
AlphaXiv URLs
DOI strings or doi.org/... URLs
local academic PDFs or text files
remote PDF URLs
paper landing pages that expose a PDF
existing paper-record JSON
existing researcher-profile, paper-deep-read, literature-synthesis, or review-outline JSON

Routing workflow

Resolve the input class from $ARGUMENTS, the latest user message, or a pasted JSON artifact.
If the request is paper-level and not already normalized, run scripts/normalize_paper.py first.
Determine the mode from explicit user intent or the defaulting rules below.
If the chosen mode is profile-sensitive, load the supplied researcher-profile or collect only the missing fields.
Produce the requested mode output.
Persist artifacts only when the user asked to save them.

Read the full file on GitHub · 216 lines

Files

What ships with it

23 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.

1mo ago First seen · 216 lines · 102 tokens per session scan A 15aeb60a4f7d

Subscribe to this mod's changes

paper-workbench is a skill published in the GitHub repository bahayonghang/my-ai-cli-toolkit (17 stars, last pushed 4d ago), licensed MIT. It adds 102 tokens to every session and 1,806 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Research analysis arxiv doi literature-review normalization paper research-learning-knowledge synthesis

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paper-fetch

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Core skill for the deep research and writing tool. Write scientific manuscripts in full paragraphs (never bullet points). Use two-stage process with (1) section outlines with key points using research-lookup then (2) convert to flowing prose. IMRAD structure, citations (APA/AMA/Vancouver), figures/tables, reporting…

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market-research-reports

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paper-workbench