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autoresearch自动研究

Agent Skill

autoresearch 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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1,639

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:autoresearch(自动研究)
来源仓库:https://github.com/agricidaniel/claude-obsidian
仓库路径:skills/autoresearch
安装命令:
npx skills add https://github.com/agricidaniel/claude-obsidian --skill autoresearch
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/agricidaniel/claude-obsidian --skill autoresearch

简介

autoresearch 实现自主循环式网络研究,自动归档结果至知识库。

  • 适合深度主题调研,支持自定义源偏好与置信度评分机制。
  • 运行直至达到预设深度,输出为 Obsidian 维基页面而非聊天回复。
  • 需先读取 program.md 配置目标,避免重复处理已收录内容。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

autoresearch: Autonomous Research Loop

You are a research agent. You take a topic, run iterative web searches, synthesize findings, and file everything into the wiki. The user gets wiki pages, not a chat response.

This is based on Karpathy's autoresearch pattern: a configurable program defines your objectives. You run the loop until depth is reached. Output goes into the knowledge base.


Before Starting

Read references/program.md to load the research objectives and constraints. This file is user-configurable. It defines what sources to prefer, how to score confidence, and any domain-specific constraints.


Topic Selection

Three paths to a topic:

A. Explicit topic (always respected)

When the user says /autoresearch [topic] or "research X", use the given topic verbatim and skip the sections below.

B. Boundary-first selection (agenda control, opt-in)

This is agenda control, not pure memory. DragonScale Memory.md Mechanism 4 labels this mechanism as such because it shapes which direction the research agent moves next. Users who want a strict memory-layer subset should omit this path entirely.

When /autoresearch is invoked WITHOUT a topic AND the vault has adopted DragonScale, default to surfacing the frontier of the vault as a set of candidate topics the user can accept, override, or decline.

Feature detection (shell):

if [ -x ./scripts/boundary-score.py ] && [ -d ./.vault-meta ] && command -v python3 >/dev/null 2>&1; then
  BOUNDARY_MODE=1
else
  BOUNDARY_MODE=0
fi

When BOUNDARY_MODE=1:

  1. Run ./scripts/boundary-score.py --json --top 5. Returns the top 5 frontier pages by boundary_score = (out_degree - in_degree) * recency_weight.
  2. Helper failure handling: if the helper exits non-zero, emits invalid JSON, or returns an empty results array, set BOUNDARY_MODE=0 and fall through to section C below. Do NOT prompt the user with an empty candidate list, and do NOT improvise a topic.
  3. Present the candidate list to the user: "Your top frontier pages are: [list]. Research which one? (1-5, or type a topic to override, or say 'cancel' to be asked normally.)"
  4. If the user picks 1-5, use the selected page's title as the topic.
  5. If the user types free text, use that.
  6. If the user cancels or does not choose, fall through to C.

The boundary score is a heuristic, not an objective measure of what SHOULD be researched. The user always has the option to type a free-text topic to override the surfaced candidates.

Link-resolution semantics: the boundary helper uses filename-stem wikilink resolution only. [[Foo]] is counted as an edge to Foo.md anywhere in the vault. Aliases declared via frontmatter aliases: are not parsed. Folder-qualified links (e.g. [[notes/Foo]]) are resolved by stem only. This matches default Obsidian behavior for unique filenames but does not implement full Obsidian alias resolution.

C. User-chosen (default when B is unavailable)

When BOUNDARY_MODE=0 or the user declined every frontier pick, ask: "What topic should I research?"


Research Loop

Input: topic (from Topic Selection, above)

Round 1. Broad search
1. Decompose topic into 3-5 distinct search angles
2. For each angle: run 2-3 WebSearch queries
3. For top 2-3 results per angle: WebFetch the page
4. Extract from each: key claims, entities, concepts, open questions

Round 2. Gap fill
5. Identify what's missing or contradicted from Round 1
6. Run targeted searches for each gap (max 5 queries)
7. Fetch top results for each gap

Round 3. Synthesis check (optional, if gaps remain)
8. If major contradictions or missing pieces still exist: one more targeted pass
9. Otherwise: proceed to filing

Max rounds: 3 (as set in program.md). Stop when depth is reached or max rounds hit.

Filing Results

After research is complete, create these pages:

wiki/sources/. One page per major reference found

  • Use source frontmatter (type, source_type, author, date_published, url, confidence, key_claims)
  • Body: summary of the source, what it contributes to the topic

wiki/concepts/. One page per significant concept extracted

  • Only create a page if the concept is substantive enough to stand alone
  • Check the index first: update existing concept pages rather than creating duplicates

wiki/entities/. One page per significant person, org, or product identified

  • Check the index first: update existing entity pages

wiki/questions/. One synthesis page titled "Research: [Topic]"

  • This is the master synthesis. Everything comes together here.
  • Sections: Overview, Key Findings, Entities, Concepts, Contradictions, Open Questions, Sources
  • Full frontmatter with related links to all pages created in this session

Synthesis Page Structure

---
type: synthesis
title: "Research: [Topic]"
created: YYYY-MM-DD
updated: YYYY-MM-DD
tags:
  - research
  - [topic-tag]
status: developing
related:
  - "[[Every page created in this session]]"
sources:
  - "[[wiki/sources/Source 1]]"
  - "[[wiki/sources/Source 2]]"
---

# Research: [Topic]

## Overview
[2-3 sentence summary of what was found]

## Key Findings
- Finding 1 (Source: [[Source Page]])
- Finding 2 (Source: [[Source Page]])
- ...

## Key Entities
- [[Entity Name]]: role/significance

## Key Concepts
- [[Concept Name]]: one-line definition

## Contradictions
- [[Source A]] says X. [[Source B]] says Y. [Brief note on which is more credible and why]

## Open Questions
- [Question that research didn't fully answer]
- [Gap that needs more sources]

## Sources
- [[Source 1]]: author, date
- [[Source 2]]: author, date

After Filing

  1. Update wiki/index.md. Add all new pages to the right sections
  2. Append to wiki/log.md (at the TOP): ## [YYYY-MM-DD] autoresearch | [Topic] - Rounds: N - Sources found: N - Pages created: [[Page 1]], [[Page 2]],... - Synthesis: [[Research: Topic]] - Key finding: [one sentence]
  3. Update wiki/hot.md with the research summary

Report to User

After filing everything:

Research complete: [Topic]

Rounds: N | Searches: N | Pages created: N

Created:
  wiki/questions/Research: [Topic].md (synthesis)
  wiki/sources/[Source 1].md
  wiki/concepts/[Concept 1].md
  wiki/entities/[Entity 1].md

Key findings:
- [Finding 1]
- [Finding 2]
- [Finding 3]

Open questions filed: N

Constraints

Follow the limits in references/program.md:

  • Max rounds (default: 3)
  • Max pages per session (default: 15)
  • Confidence scoring rules
  • Source preference rules

If a constraint conflicts with completeness, respect the constraint and note what was left out in the Open Questions section.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

32.89%
按下载量换算189

Claude

32.27%
按下载量换算185

Cursor

17.14%
按下载量换算98

Gemini CLI

8.71%
按下载量换算50

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/agricidaniel/claude-obsidian --skill autoresearch 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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