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obsidian-project-memoryObsidian project 记忆

Agent Skill

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。

总安装

1,148

周安装

46

GitHub Stars

3,477

下载量

372
CodexClaudeCursorGemini CLI

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: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

简介

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。

SKILL.md

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

适合场景

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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

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

external-service

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

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来源信息

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