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Agent Skill · 研究检索

obsidian-project-memory(Obsidian project 记忆)

obsidian-project-memory 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。

obsidian-project-memory 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 41,736。

总安装 1,148周安装 46GitHub Stars 3,477下载 372核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:obsidian-project-memory(Obsidian project 记忆)
来源仓库:https://github.com/galaxy-dawn/claude-scholar
仓库路径:skills/obsidian-project-memory
安装命令:
npx skills add https://github.com/galaxy-dawn/claude-scholar --skill obsidian-project-memory
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/galaxy-dawn/claude-scholar --skill obsidian-project-memory

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。支持基于关键词、任务场景或来源线索进行信息检索与筛选。通过 npx skills add 命令从指定 GitHub 仓库安装使用。安装前需确认权限范围、维护状态及是否涉及联网或文件操作。

obsidian-project-memory 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/obsidian-project-memory

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/galaxy-dawn/claude-scholar --skill obsidian-pr…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

obsidian-project-memory 怎么安装?

在终端执行 npx skills add https://github.com/galaxy-dawn/claude-scholar --skill obsidian-project-memo…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

obsidian-project-memory 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

obsidian-project-memory 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

obsidian-project-memory 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

obsidian-project-memory 用的人多吗?

公开数据是累计安装 1,148 次,近一周安装 46 次,下载 372 次,GitHub 3,477 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

obsidian-project-memory 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 3,477 星,维护活跃度相对可查。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
obsidian-project-memory

Obsidian project 记忆 · 本页

1,1483,477调用外部服务未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Obsidian Project Memory

Maintain a filesystem-first, agent-driven Obsidian knowledge base for a research project.

Default note output language follows the project's configured note_language; if no note language is configured, default to English. Keep technical terms, paper titles, and established folder names in their original form when that is clearer. Only switch note prose to another language when the user explicitly asks.

Prefer this skill when working inside a repository that:

  • already contains .claude/project-memory/registry.yaml, or
  • clearly looks like a research project and should be bound to an Obsidian vault.

Core principles

  • Use scripts for project state management.
  • Use agents for project understanding and synthesis.
  • Write only durable research knowledge into a small vault structure.
  • Do not require MCP, API keys, REST plugins, or .base artifacts.
  • Do not depend on .canvas globally, but allow literature workflows to maintain Maps/literature.canvas as a default literature graph artifact.
  • Treat internal experiment summary reports as durable result-facing notes under Results/Reports/, not as Writing/ notes.

Default vault structure

Write into this project layout only:

Research/{project-slug}/
  00-Hub.md
  01-Plan.md
  Knowledge/
  Papers/
  Experiments/
  Results/
    Reports/
  Writing/
  Daily/
  Archive/

Read references/SCHEMA.md for the exact structure and note roles.

Deterministic helper script

Use scripts/project_kb.py only for low-freedom operations such as detect, bootstrap, sync, and lifecycle management:

python3 scripts/project_kb.py detect --cwd "$PWD"
python3 scripts/project_kb.py bootstrap --cwd "$PWD" --vault-path "$OBSIDIAN_VAULT_PATH"
python3 scripts/project_kb.py sync --cwd "$PWD" --scope auto
python3 scripts/project_kb.py lifecycle --cwd "$PWD" --mode archive
python3 scripts/project_kb.py query-context --cwd "$PWD" --kind broad
python3 scripts/project_kb.py query-context --cwd "$PWD" --kind experiment --query freezing
python3 scripts/project_kb.py find-canonical-note --cwd "$PWD" --kind experiment --query freezing
python3 scripts/project_kb.py note-lifecycle --cwd "$PWD" --mode archive --note "Results/Old-Result.md"

Do not expect the script to understand project meaning. It manages state; it does not replace synthesis.

Read references/SCRIPT-VS-AGENT.md when deciding whether a task belongs in the script or must stay agent-driven.

Default workflow

1. Detect and bind

  1. Run scripts/project_kb.py detect --cwd "$PWD".
  2. If the repo is already bound, continue with the existing project.
  3. If the repo is not yet bound but is a strong research-project candidate, bootstrap it with project_kb.py bootstrap.

For the detailed lifecycle, read references/WORKFLOW.md.

2. Read the minimum context

Before writing anything, read only the minimum stable context:

  • .claude/project-memory/<project_id>.md
  • 00-Hub.md
  • 01-Plan.md
  • today's Daily/YYYY-MM-DD.md if it exists

If the task is about project understanding, existing docs, or historical results, load more context selectively using the references below.

3. Classify the knowledge delta

Route the current turn into one or more of these buckets:

  • knowledge
  • paper
  • experiment
  • result
  • writing
  • daily
  • project-structure

Read references/NOTE-ROUTING.md before writing.

4. Follow the default durable research path

Default path for substantive research work:

  • Papers/ -> extract reusable ideas, baselines, and project relevance
  • Experiments/ -> turn those into testable hypotheses, runbooks, or ablations
  • Results/ -> promote stable findings with evidence and interpretation
  • Results/Reports/ -> store one round or one batch's internal experiment report when a complete retrospective has been written
  • Writing/ -> externalize durable claims into reviews, proposals, drafts, slides, or rebuttal notes

Use Daily/ as chronology and staging, not the final home for durable research knowledge.

Read references/PAPERS-TO-WRITING.md when deciding how a turn should advance along this path.

5. Decide whether agent-first synthesis is required

Use agent-first import/synthesis when:

  • importing an existing repository for the first time,
  • the user says the knowledge base is empty or lacks background,
  • multiple source documents must be synthesized into stable project knowledge,
  • the project needs a durable overview, research questions, experiment map, or results summary.

In these cases, first use an agent to read key sources, then write the synthesized result back into Obsidian.

Read references/AGENT-FIRST-IMPORT.md for the recommended source-reading order.

6. Write back minimally

Always keep write-back conservative.

Write back at least:

  • today's Daily/YYYY-MM-DD.md when this turn changes project state,
  • 00-Hub.md only when recent progress or top-level status truly changes,
  • .claude/project-memory/<project_id>.md when project state changes.

Then write only the durable note that matches the bucket:

  • knowledge -> Knowledge/
  • paper -> Papers/
  • experiment -> Experiments/
  • result -> Results/
  • writing -> Writing/
  • daily -> Daily/
  • project-structure -> usually Knowledge/Project-Overview.md or Knowledge/Source-Inventory.md

Internal experiment round reports should default to:

  • Results/Reports/YYYY-MM-DD--{experiment-line}--r{round}--{purpose}.md

Read references/NOTE-TEMPLATES.md when a note needs a stable shape.

Knowledge CRUD rules

Treat the vault as a small set of canonical notes plus supporting daily context.

Create

  • Ingest new knowledge deliberately; do not equate every new Markdown file with a durable note.
  • Keep one canonical note per durable object whenever possible:

- one stable project overview, - one stable experiment note per experiment line, - one stable result note per durable finding, - one stable paper note per paper.

  • For new Markdown files, default to summarize first, then route:

- promote directly only when the file is already stable and self-contained, - otherwise merge into an existing canonical note or stage it in Daily/.

  • If the new durable object is a full internal experiment report, store it under Results/Reports/ and link the matching Experiments/ and canonical Results/ notes.

Read

  • Query narrowly first:

- broad project questions -> 00-Hub.md + key Knowledge/ notes, - active work questions -> 01-Plan.md + today's Daily/ + project memory, - specific experiment/result/paper questions -> the matching canonical note first, - specific internal experiment retrospective -> the matching note in Results/Reports/ first.

  • Use agent synthesis only when the answer spans multiple durable sources or still depends on repo material after reading canonical notes.

Update

  • Prefer updating an existing canonical note over creating a sibling note.
  • Treat raw material as input, not as a final vault object.
  • Allow fast append-only logging in Daily/, but keep durable knowledge in Knowledge/, Papers/, Experiments/, Results/, Results/Reports/, or Writing/.

Delete

  • Treat “remove”, “delete”, or “stop using” as archive by default.
  • Purge only when the user explicitly asks for permanent deletion.
  • When archiving or purging a durable note, repair direct links in 00-Hub.md, 01-Plan.md, and explicit index notes so the main working surface does not point to missing files.

Safety rules

  • Do not mirror the whole repository into the vault.
  • Do not generate empty folder taxonomies or placeholder notes without real content.
  • Do not write every repo delta into a new note.
  • Do not treat every code change as a knowledge update.
  • Do not create .base files unless the user explicitly asks for them.
  • Do not create arbitrary .canvas sprawl; the main default exception is Maps/literature.canvas for literature workflows.
  • For engineering-only turns, prefer Daily/ plus project memory unless there is a real experiment, result, or planning impact.
  • Treat “remove project knowledge” as archive by default; purge only when the user explicitly asks for permanent deletion.

Reference files

Load only what is needed:

  • references/SCHEMA.md - vault structure and note roles
  • references/WORKFLOW.md - detect/bootstrap/sync/archive workflow
  • references/PAPERS-TO-WRITING.md - default handoff from literature to experiments, results, and writing
  • references/SCRIPT-VS-AGENT.md - boundary between low-freedom script operations and agent-only reasoning
  • references/KNOWLEDGE-CRUD.md - create/read/update/delete rules for durable research knowledge
  • references/NOTE-ROUTING.md - where each kind of knowledge should go
  • references/NEW-MD-INGESTION.md - how to ingest a newly created Markdown file
  • references/AGENT-FIRST-IMPORT.md - how to import an existing project with agent synthesis
  • references/NOTE-TEMPLATES.md - lightweight note shapes for common note types

平台分布

Codex

37.58%
按下载量换算140

Claude

30.8%
按下载量换算115

Cursor

16.94%
按下载量换算63

Gemini CLI

8.45%
按下载量换算31

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。目前只有一个公开来源,建议同时核对源仓库。

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