empiricalwiki: Skill for Claude Code

.claude/skills/survey/SKILL.md

survey is a skill for Claude Code from Lambenthan/empiricalwiki. It costs 35 tokens per session (2,593 once invoked), scanned A, original, MIT.

A research-writing tool that turns notes from a local knowledge wiki into a Related Work section, which explains how earlier studies connect to your paper. It can produce LaTeX or Markdown.

In plain words
What is it for?
Use it to group studies by research direction, build a connected narrative, explain how each group differs from your work, and save the result for a paper or wiki.
Why use it?
It removes the need to search through separate paper, concept, and topic notes and organise them manually. It also applies the wiki's citation and academic-writing rules.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: reads .claude/ paths; mentions Claude Code.

This is Lambenthan/empiricalwiki's own configuration. It tells Claude Code how to work on empiricalwiki itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything empiricalwiki configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 tools/research_wiki.py slug "<query-keywords>".

Reuse

Borrowing it

Nothing to install: this file belongs to Lambenthan/empiricalwiki. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Lambenthan/empiricalwiki/main/.claude/skills/survey/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/Lambenthan/empiricalwiki

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.

agentmods badge for survey

README.md
[![agentmods](https://agentmods.dev/badge/skills/lambenthan/empiricalwiki/survey/github.svg)](https://agentmods.dev/skills/lambenthan/empiricalwiki/survey)
Your own site
<a href="https://agentmods.dev/skills/lambenthan/empiricalwiki/survey"><img src="https://agentmods.dev/badge/skills/lambenthan/empiricalwiki/survey/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 survey

Your own site · 80×15
<a href="https://agentmods.dev/skills/lambenthan/empiricalwiki/survey"><img src="https://agentmods.dev/badge/skills/lambenthan/empiricalwiki/survey.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,593 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 $0.00035 $0.02593
Opus 5 $0.00017 $0.01296
Sonnet 5 $0.00007 $0.00519
Haiku 4.5 $0.00003 $0.00259

Measured 9d ago against content hash 2a5a9a6ef0a9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

survey 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 9d 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.

.claude/skills/survey/SKILL.md · 217 lines

How it starts

The opening of the file, as written. The whole thing — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/survey

基于 wiki 已有知识,生成可直接用于论文的 Related Work 章节。 从 wiki/papers/、concepts/、topics/ 取材,按研究方向分组(非逐篇罗列), 每组以「与本文的区别」收尾。引用遵循 citation-verification.md, 写作遵循 academic-writing.md 的 Related Work 规则。 支持 LaTeX 和 Markdown 两种输出格式。

Inputs

  • query:以下之一:
    • 研究问题描述(自由文本,如 "parameter-efficient fine-tuning for LLMs")
    • claim slugs 列表(从 wiki/claims/ 中,用于围绕特定 claims 组织相关工作)
    • PAPER_PLAN.md 路径(从中提取 Related Work section 定义)
  • --format(可选,默认 latex):输出格式
    • latex\cite{key} 引用,可直接嵌入论文
    • markdown[[slug]] wikilink 引用,用于 wiki 存档
  • --max-papers(可选,默认 30):最多引用的论文数量

Outputs

  • wiki/outputs/related-work-{slug}-{date}.md — Related Work 文本(归档)
  • wiki/graph/edges.jsonl — derived_from 边(若新建 output)
  • wiki/log.md — 追加日志
  • 终端输出 — Related Work 正文(方便直接复制)

Wiki Interaction

Reads

  • wiki/papers/*.md — Problem、Key idea、Results、Related、My take
  • wiki/concepts/*.md — Definition、Variants、Comparison、Known limitations
  • wiki/topics/*.md — Overview、Timeline、Open problems、Seminal works
  • wiki/claims/*.md — Statement、source_papers(若输入为 claim slugs)
  • wiki/ideas/*.md — Motivation(了解本文定位)
  • wiki/index.md — 内容目录,按 importance 筛选
  • wiki/graph/context_brief.md — 全局上下文
  • wiki/graph/edges.jsonl — 论文间语义关系(same_problem_as、similar_method_to、complementary_to、builds_on、compares_against、improves_on、challenges、surveys)
  • .claude/skills/shared-references/academic-writing.md — Related Work 写作规则
  • .claude/skills/shared-references/citation-verification.md — 引用纪律

Writes

  • wiki/outputs/related-work-{slug}-{date}.md — 归档文件
  • wiki/graph/edges.jsonl — derived_from 边
  • wiki/log.md — 追加操作日志

Graph edges created

  • derived_from:related-work output → source papers

Workflow

前置:确认工作目录为 wiki 项目根(包含 wiki/raw/tools/ 的目录)。

Step 1: 定位相关知识

  1. 解析输入
    • 若为自由文本:提取关键词,在 wiki/index.md 中匹配 tags 和 titles
    • 若为 claim slugs:读取每个 claim 的 source_papers,收集相关论文
    • 若为 PAPER_PLAN 路径:读取 Related Work section 的 groupings 和 citations
  2. 读取 wiki/graph/context_brief.md 获取全局上下文
  3. 读取 wiki/graph/edges.jsonl:提取论文间语义关系(same_problem_as、similar_method_to、complementary_to、builds_on、compares_against、improves_on、challenges、surveys)
  4. 生成候选论文列表
    • 从 index.md 按 importance 降序排列
    • 按 tags 和 domain 匹配度排序
    • 限制为 --max-papers
  5. 若候选论文 < 5 篇:警告「相关论文不足,建议先 /ingest 更多论文」

Read the full file on GitHub · 217 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. 9d ago First seen · 217 lines · 35 tokens per session scan A 2a5a9a6ef0a9

Subscribe to this mod's changes

survey is a skill published in the GitHub repository Lambenthan/empiricalwiki (82 stars, last pushed 2mo ago), licensed MIT. It adds 35 tokens to every session and 2,593 once invoked, about $0.0002 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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