literature-scout-zh

literature-scout-zh is a skill for Claude Code, Codex from gy910210/hermes-research-skills. It costs 85 tokens per session (1,458 once invoked), scanned A, original, MIT.

A Chinese-language research helper that finds recent papers, benchmarks, datasets, official blogs, and other trusted technical sources about a topic. It organizes the findings into an evidence map, topic groups, and leads for supporting or conflicting evidence.

In plain words
What is it for?
Use it to update a research brief, investigate a topic from the past year or a chosen period, find benchmark or dataset releases, and build a reading queue from academic, industry, and official sources.
Why use it?
It reduces the time spent searching for current sources and checking whether an existing report or literature collection is out of date. It also helps reveal missing evidence and disagreements between sources.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to update a research brief, investigate a topic from the past year or a chosen period, find benchmark or dataset releases, and build a reading queue from academic, industry, and official sources.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/gy910210/hermes-research-skills/literature-scout-zh
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 gy910210/hermes-research-skills --skill literature-scout-zh
Clone the repo
git clone --depth 1 https://github.com/gy910210/hermes-research-skills

Made for: Claude Code, Codex.

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 literature-scout-zh

README.md
[![agentmods](https://agentmods.dev/badge/skills/gy910210/hermes-research-skills/literature-scout-zh/github.svg)](https://agentmods.dev/skills/gy910210/hermes-research-skills/literature-scout-zh)
Your own site
<a href="https://agentmods.dev/skills/gy910210/hermes-research-skills/literature-scout-zh"><img src="https://agentmods.dev/badge/skills/gy910210/hermes-research-skills/literature-scout-zh/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.

agentmods 80×15 button for literature-scout-zh

Your own site · 80×15
<a href="https://agentmods.dev/skills/gy910210/hermes-research-skills/literature-scout-zh"><img src="https://agentmods.dev/badge/skills/gy910210/hermes-research-skills/literature-scout-zh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,458 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00085 $0.01458
Opus 5 $0.00043 $0.00729
Sonnet 5 $0.00017 $0.00292
Haiku 4.5 $0.00009 $0.00146

Measured 12d ago against content hash 692b0a6e2e54, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

literature-scout-zh 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 12d 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.

skills/literature-scout-zh/SKILL.md · 107 lines

How it starts

The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Hermes 适配说明

  • 本 skill 现面向 Hermes 使用,优先依赖 Hermes 原生工具:search_filesread_filewrite_filepatchsession_searchdelegate_taskcronjobbrowserweb/searchvision
  • 若正文提到 references/...scripts/...,优先读取当前 skill 目录下对应文件,不再依赖 Claude 专属目录结构。
  • 原始 Claude agents/openai.yaml 不作为执行前提;需要并行研究、分工精读或角色评审时,改用 Hermes 的 delegate_task
  • 保留原有研究方法论与产物契约,但执行层统一按 Hermes 工具体系落地。

Literature Scout(中文)

这个 skill 负责“扩展检索 + 证据地图”,不是单篇精读器。

何时使用

  • 已有 brief 或旧报告,需要继续找新论文和新证据。
  • 要围绕一个子方向做近一年检索。
  • 要找支持证据、反例、benchmark、数据集 release 状态或产业官方信号。

输入

  • context_brief 或主题问题
  • time_window:优先最近一年;若用户指定则按指定范围
  • result_budget:默认只保留高价值结果
  • source_mixacademic / industrial / official 的偏好
  • search_mode
    • fresh_scan
    • institution_line
    • citation_neighborhood
    • diff_against_catalog
    • bridge_line
    • artifact_hunt

输出

  • evidence_map
  • candidate_clusters
  • support_vs_contradiction_seeds
  • priority_reading_queue
  • missing_from_catalog
  • institution_clusters
  • citation_frontier
  • route_family_candidates

工作流

  1. 先从 context_brief 提取方向、术语、已有结论与未解问题。
  2. ../research-orchestrator-zh/references/source-tiering.md 选择来源优先级。
  3. 每条结果都要标注:
    • direct / adjacent / background
    • academic / industrial / official
    • public benchmark / private data / unknown release
    • support / contradiction / open gap
  4. 去重后按方向聚类,而不是只给一长串论文。
  5. 优先输出“为什么值得继续读”的队列:哪些能直接改主稿,哪些更适合作为旁证或潜力方向。
  6. 如果 search_mode=diff_against_catalog,额外读取现有 awesome-*.md 或 curated repo 页面,识别:
    • 支持文档里有但 catalog 里没有
    • 同一论文是否已被重复收录
    • 哪些新条目只够做 watchlist
  7. 如果 search_mode=institution_line,优先按机构/平台/团队聚类输出,而不是只按技术树输出。
  8. 如果 search_mode=citation_neighborhood,优先围绕核心种子论文的引用邻域和同机构家族继续扩展。
  9. 如果 search_mode=bridge_line,优先找“概念桥接”论文:它们不一定是主线核心论文,但能解释两个研究家族之间的结构关系。
  10. 如果 search_mode=artifact_hunt,优先寻找附录、prompt template、训练表格、数据构造细节、ratio 披露和公开示例,而不只找新论文标题。

守护

  • 不把搜索结果列表冒充成综合结论。
  • 不因为“新”就高优先;优先级看与主题的直接性、来源可靠性与复用价值。
  • 数据集、benchmark、release 状态没有明确来源时标 unknown

Read the full file on GitHub · 107 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. 12d ago First seen · 107 lines · 85 tokens per session scan A 692b0a6e2e54

Subscribe to this mod's changes

literature-scout-zh is a skill published in the GitHub repository gy910210/hermes-research-skills (2 stars, last pushed 4mo ago), licensed MIT. It adds 85 tokens to every session and 1,458 once invoked, about $0.0004 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.

Related

Other skills, from other repositories

b2b-sdr-agent

Autonomous AI Sales Development Rep for B2B export — handles lead discovery, BANT qualification, multi-channel outreach (WhatsApp/Email/Telegram), CRM management, and deal pipeline tracking. Built for cross-border trade.

iPythoning/b2b-sdr-hermes-skill · 52 tokens

loop-engineering

Loop Engineering framework: design autonomous agent feedback cycles instead of hand-prompting each step.

lunkerchen/loop-engineering-skill · 21 tokens

fablize

A harness that makes any model see a task through to the end — with evidence and verification — as procedure, not as luck. Enforces verification grounding (run & observe artifacts before declaring done), multi-story decomposition with an evidence gate, a systematic investigation protocol, and early-stop prevention.…

teixeirazeus/fablize-for-hermes · 79 tokens

browser-harness-ats-automation

Automate job applications on ATS platforms (Ashby, Greenhouse, Workday) using browser-use/browser-harness with CDP. Covers iframe session management, file upload, hidden checkbox handling, and known reCAPTCHA/S3 blockers.

arimanyus/hermes-merchant · 56 tokens

job-scraper-pipeline

Automated ML/AI job scraping, deduplication, and gatekeeper scoring pipeline. Scrapes AI company career pages on Greenhouse, AshbyHQ, and Lever, avoids duplicates, and scores jobs 0-100 against profile keywords, classifying tier-1/2/3.

arimanyus/hermes-merchant · 66 tokens

greenhouse-job-application

Automate filling job applications on Greenhouse.io and similar React-based ATS platforms via browser automation. Covers React input handling, reCAPTCHA detection, resume upload limitations, and single-expression multi-field filling.

arimanyus/hermes-merchant · 46 tokens