deep-lit-reader

deep-lit-reader is an agent for Claude Code from AutoResearch-Factory/Agon. It costs 26 tokens per session (2,878 once invoked), scanned A, original, MIT.

An agent workflow for reading one arXiv research paper in depth, writing a wiki note, and producing a structured result file. arXiv is a public online repository for research papers.

In plain words
What is it for?
Use it to study an arXiv paper, extract a substantial literature note, assess its originality, and emit the required JSON result.
Why use it?
It enforces a detailed, traceable reading process that checks the paper’s claims, novelty, files, and recent related work.

Agent for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Installs and runs on its own, but its text points at files inside its plugin — anything it tells you to read at a ${CLAUDE_PLUGIN_ROOT} path is only there once the plugin is installed. Installing the plugin gets both.

Part of the agon plugin — 5 skills, 4 commands, 12 agents, 2 hooks shipped together

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 agents/autoresearch-factory/agon/deep-lit-reader
Clone the repo
git clone --depth 1 https://github.com/AutoResearch-Factory/Agon

Made for: Claude Code.

Or install agon, the plugin that ships this one along with the rest of its 5 skills, 4 commands, 12 agents, 2 hooks.

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.

agentmods badge for deep-lit-reader

README.md
[![agentmods](https://agentmods.dev/badge/agents/autoresearch-factory/agon/deep-lit-reader.svg)](https://agentmods.dev/agents/autoresearch-factory/agon/deep-lit-reader)
Your own site
<a href="https://agentmods.dev/agents/autoresearch-factory/agon/deep-lit-reader"><img src="https://agentmods.dev/badge/agents/autoresearch-factory/agon/deep-lit-reader.svg" alt="Measured on agentmods" height="20"></a>
Per session 26 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,878 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 5.1 $0.00026 $0.02878
Opus 5 $0.00013 $0.01439
Sonnet 5 $0.00005 $0.00576
Haiku 4.5 $0.00003 $0.00288

Measured 6d ago against content hash be4cb5914c19, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

deep-lit-reader 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.

agents/deep-lit-reader.md · 215 lines

How it starts

The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.

开始工作前,必须 Read 以下 refinery 技能文件(跳过视为任务失败):

  • ${CLAUDE_PLUGIN_ROOT}/skills_aris/literature-survey.md — 文献调研 mindset:论文应该读什么、结构 gap 模式、per-paper 分析
  • ${CLAUDE_PLUGIN_ROOT}/skills_aris/novelty-check.md — 创新性审查 mindset:分解到 claim 级别、诚实规则、查最近 6 个月 arXiv、同时查方法和实验 setting

<absolute_red_lines> 以下规则违反任意一条即视为任务失败:

  1. 所有文献操作必须通过 arxiv-tools skill 提供的 arxiv_tool.py。禁止编造论文、禁止凭记忆引用、禁止使用其他搜索工具。
  2. 读 tex 前必须先用 wc -l 检查每个 .tex 文件的总行数。行数 > 800 的文件必须分段读完(offset 逐段推进),不得遗漏任何一行。
  3. 读完所有文件后,必须在 thinking 中汇总"已读 X 个文件 / 共 Y 行",核对与 wc -l 的总和一致。
  4. wiki 精华提炼部分必须 ≥ 50 行 markdown。写短了等于白读。
  5. 任务完成后必须写 /tmp/$USER/<topic_slug>-deep-lit-reader-<arxiv_id>-result.json,包含 statussummary 字段。没有这个文件 dispatcher 无法收集结果。
  6. 禁止向 /tmp 写任何其他文件。 禁止 git clone、禁止下载 PDF/txt 到 /tmp、禁止在 /tmp 下创建目录。非 arxiv 来源(GitHub 仓库等)只用 WebFetch 在线读,不下载到本地。 </absolute_red_lines>

<tool_policy> 所有文献操作必须通过 arxiv-tools skill 提供的 arxiv_tool.py。禁止凭记忆编造论文。

开工前先用 Skill 工具加载 agon:arxiv-tools,skill 输出会给出本机 arxiv_tool.py 的绝对路径和各子命令用法。后续所有 arxiv 调用都按 skill 给出的命令格式跑(下文示例省略绝对路径,实跑时替换成 skill 给的)。

常用命令:

  • 下载 tex → uv run arxiv_tool.py tex <arxiv_id>
  • 获取引文 → uv run arxiv_tool.py references <arxiv_id>
  • 获取反引文(仅 S2)→ uv run arxiv_tool.py cited <arxiv_id> --source s2

需要读文件内容 → Read。下载 tex 前先确认 tex 未缓存。工具结果回来后再分析。 </tool_policy>

第一步:检查是否已读

读入传入的 <arxiv_id><topic_slug>。参数从 dispatcher 的 prompt 中提取。

这是可 resume 任务。已有 wiki、已有下载 tex、已有审读章节都必须复用,不要重复下载或重复写同一 topic 的 Read by 章节。

用 Bash 检查 wiki 文件是否已存在(wiki 全部写入 $ARXIV_WIKI_DIR/ 指定的目录;禁止从缓存目录、其他环境变量或默认路径推断):

ls "$ARXIV_WIKI_DIR/<arxiv_id>.md" 2>/dev/null && echo "EXISTS" || echo "NOT_FOUND"

如果 EXISTS:

  • Read wiki 文件内容
  • 如果文件中包含 ## Read by: <topic_slug> → 已读。直接写 result JSON 并停止。
  • 如果没有这个章节 → wiki 存在但本 topic 没读过,继续到读全文步骤。

如果 NOT_FOUND → 继续。

第二步:下载并验证 tex 源码

运行 uv run arxiv_tool.py tex <arxiv_id>(路径以 skill 输出为准)。

如果下载失败(exit code ≠ 0,或输出中无 tex 目录)→ 写 result JSON {"status": "tex_download_failed", "arxiv_id": "...", "summary": "...", "error": "..."} 并停止。

Read the full file on GitHub · 215 lines

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. 6d ago First seen · 215 lines · 0 tokens per session scan A be4cb5914c19

Subscribe to this mod's changes

deep-lit-reader is an agent published in the GitHub repository AutoResearch-Factory/Agon (47 stars, last pushed 12d ago), licensed MIT. It adds 26 tokens to every session and 2,878 once invoked, about $0.0001 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 2026-08-30.

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