empiricalwiki: Skill for Claude Code

.claude/skills/ask/SKILL.md

ask is a skill for Claude Code from Lambenthan/empiricalwiki. It costs 20 tokens per session (2,720 once invoked), scanned A, original, MIT.

A question-and-answer workflow for searching a local wiki and combining related pages into an answer. A wiki is a linked collection of project notes, papers, concepts, claims, and research records.

In plain words
What is it for?
Use it to ask research questions, retrieve supporting pages, receive answers with wiki references, and optionally save the result as an output, concept, or claim page.
Why use it?
It saves time when an answer depends on information spread across many wiki pages. An optional crystallize mode preserves a useful answer as a new page and updates the wiki’s links.

Skill for Claude Code

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

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 rebuild-context-brief wiki/.

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/ask/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 ask

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/lambenthan/empiricalwiki/ask"><img src="https://agentmods.dev/badge/skills/lambenthan/empiricalwiki/ask.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,720 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 $0.00020 $0.02720
Opus 5.5 $0.00008 $0.01088
Sonnet 5.5 $0.00004 $0.00544
Haiku 4.5 $0.00002 $0.00272

Measured 1mo ago against content hash b5d9de181628, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ask 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 1mo 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/ask/SKILL.md · 211 lines

How it starts

The opening of the file, as written. The whole thing — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/ask

对 wiki 知识库提问。LLM 读取 context_brief.md 获取全局上下文,检索相关页面, 综合回答并附带引用。好的回答可以 crystallize 回 wiki——写入 outputs/ 或创建新的 concept/claim 页面,让探索成果像 ingest 一样持续积累。

Inputs

  • question:自然语言问题(如 "LoRA 和 Adapter 的核心区别是什么?")
  • --crystallize(可选):若指定,将回答 crystallize 回 wiki(默认仅回答不写入)
  • --format(可选):输出格式,默认 markdown,可选 table / timeline / bullets

Outputs

  • 始终:终端输出综合回答(含 [[slug]] 引用)
  • 若 crystallize:
    • wiki/outputs/{query-slug}.md — 查询结果页面(默认 crystallize 目标)
    • 或 wiki/concepts/{slug}.md — 若回答揭示了新的跨论文概念
    • 或 wiki/claims/{slug}.md — 若回答发现了可验证的新断言
    • 更新的 wiki/graph/edges.jsonl(crystallize 产生的关系)
    • 更新的 wiki/index.md 和 wiki/log.md

Wiki Interaction

Reads

  • wiki/graph/context_brief.md — 全局压缩上下文(claims, gaps, failed ideas, papers, edges)
  • wiki/index.md — 页面目录,用于定位相关页面
  • wiki/graph/open_questions.md — 开放问题,辅助判断问题是否涉及已知知识缺口
  • wiki/papers/*.md — 与问题相关的论文页面
  • wiki/concepts/*.md — 与问题相关的概念页面
  • wiki/claims/*.md — 与问题相关的 claim 页面
  • wiki/topics/*.md — 与问题相关的 topic 页面
  • wiki/people/*.md — 若问题涉及特定研究者
  • wiki/ideas/*.md — 若问题涉及研究想法或 failed ideas
  • wiki/experiments/*.md — 若问题涉及实验结果
  • wiki/Summary/*.md — 若问题涉及领域全景

Writes(仅 crystallize 模式)

  • wiki/outputs/{query-slug}.md — CREATE(查询结果页面)
  • wiki/concepts/{slug}.md — CREATE(新发现概念)或 EDIT(补充已有概念)
  • wiki/claims/{slug}.md — CREATE(新发现断言)或 EDIT(补充 evidence)
  • wiki/graph/edges.jsonl — APPEND(crystallize 产生的关系)
  • wiki/graph/context_brief.md — REBUILD(若 crystallize 创建了新页面)
  • wiki/graph/open_questions.md — REBUILD(若 crystallize 创建了新页面)
  • wiki/index.md — EDIT(若 crystallize 创建了新页面)
  • wiki/log.md — APPEND

Graph edges created(仅 crystallize)

  • output → paper: derived_from(回答引用的论文)
  • output → concept: derived_from(回答引用的概念)
  • output → claim: derived_from(回答引用的 claim)
  • concept → paper: supports(若新概念从论文中归纳)
  • claim → paper: supports(若新 claim 从论文中提取)

Workflow

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

Step 1: 加载全局上下文

Read the full file on GitHub · 211 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. 1mo ago First seen · 211 lines · 20 tokens per session scan A b5d9de181628

Subscribe to this mod's changes

ask is a skill published in the GitHub repository Lambenthan/empiricalwiki (96 stars, last pushed 4mo ago), licensed MIT. It adds 20 tokens to every session and 2,720 once invoked, about $0.0001 per session on Opus 5.5. 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.