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Agent Skill · 研究检索

context-network(上下文网络)

context-network 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。

context-network 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,权限为需要联网;许可证为 MIT,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 19,061。

总安装 5,779周安装 250GitHub Stars 67下载 1,720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
MIT

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:context-network(上下文网络)
来源仓库:https://github.com/jwynia/agent-skills
仓库路径:skills/context-network
安装命令:
npx skills add https://github.com/jwynia/agent-skills --skill context-network
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/jwynia/agent-skills --skill context-network

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。

context-network 帮助用户构建和维护结构化项目知识框架,支持跨会话的知识延续。核心目标是显式化隐性知识,通过关系建模提升信息可发现性和导航效率。提供脚手架生成和内容决策指导,平衡完整性与实用性。安装前建议确认权限范围、维护状态,以及是否会触发文件创建或内容写入操作。

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。

来源仓库内路径:skills/context-network

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/jwynia/agent-skills --skill context-network;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

    它需要需要联网,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

context-network 怎么安装?

在终端执行 npx skills add https://github.com/jwynia/agent-skills --skill context-network。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

context-network 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。

context-network 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

context-network 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

context-network 用的人多吗?

公开数据是累计安装 5,779 次,近一周安装 250 次,下载 1,720 次,GitHub 67 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。

context-network 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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 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
context-network

上下文网络 · 本页

5,77967需要联网MIT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

Context Network Lifecycle

You help users build and maintain context networks—structured frameworks for organizing project knowledge that persist across sessions and support both human and agent work. Your role is to diagnose context network state, generate appropriate scaffolding, and coach users on content decisions.

Core Principle

Context networks make relationships explicit. Implicit knowledge doesn't survive session boundaries. Structure enables discovery. The goal is not completeness but navigability.

Quick Reference

Use this skill when:

  • Starting a new project that needs persistent context
  • Existing documentation feels scattered or hard to navigate
  • Agent effectiveness is degrading due to missing context
  • Context-retrospective identified gaps to address

Key states:

  • CN0: No Network - Project has no context network
  • CN1: Scattered Docs - Documentation exists but isn't organized as a network
  • CN2: Siloed Structure - Structure exists but connections missing
  • CN3: Navigation Broken - Connections exist but hard to traverse
  • CN4: Guidance Unclear - Structure works but agent instructions fail
  • CN5: Relationships Missing - Impacts/dependencies undocumented
  • CN6: Maintenance Failing - Network exists but drifts from reality

The States

State CN0: No Network

Symptoms: No .context-network.md file. No context/ directory. Documentation scattered in README or absent entirely. Agent asks same questions each session.

Key Questions:

  • What type of project is this? (software, research, creative, personal knowledge)
  • Who will use this context? (solo, team, agents)
  • What's the expected lifespan?

Interventions:

  • Run Bootstrap Mode (see below)
  • Generate discovery file and initial structure
  • Coach on minimal viable content

State CN1: Scattered Docs

Symptoms: README.md has grown unwieldy. docs/ folder exists but files aren't connected. Architecture decisions buried in comments or commit messages. Agent finds partial info but misses connections.

Key Questions:

  • What documentation already exists?
  • Which docs are still accurate?
  • What relationships exist between these documents?

Interventions:

  • Scan for existing documentation
  • Propose migration plan to context network structure
  • Generate relationship mappings for migrated content

State CN2: Siloed Structure

Symptoms: Context network exists with clear directory structure. Files are well-organized within domains. But cross-references are sparse. Agent finds info within domains but misses cross-domain implications.

Key Questions:

  • Which domains affect each other?
  • What changes in A typically require changes in B?
  • Are there shared concepts with different names in different domains?

Interventions:

  • Generate relationship templates
  • Coach on identifying cross-domain connections
  • Create hub documents that bridge domains

State CN3: Navigation Broken

Symptoms: Information exists and is connected, but hard to find. status.md is stale. No clear entry points for common tasks. Agent reads many files to find what it needs.

Key Questions:

  • What are the most common tasks agents perform?
  • Which files get read most often? Least often?
  • Are there orphan documents no one accesses?

Interventions:

  • Create/update hub documents
  • Establish task-based navigation guides
  • Prune or consolidate orphan content

State CN4: Guidance Unclear

Symptoms: Context network is well-structured. CLAUDE.md exists but agents still make wrong decisions. Instructions exist but aren't followed. Agent behavior inconsistent with documented patterns.

Key Questions:

  • Which agent behaviors are problematic?
  • Are instructions ambiguous or contradictory?
  • Is guidance too abstract to act on?

Interventions:

  • Refine CLAUDE.md with specific, actionable instructions
  • Add examples to abstract guidance
  • Create decision trees for common choices

State CN5: Relationships Missing

Symptoms: Changes in one area unexpectedly break another. Dependencies discovered mid-task. Impact of decisions unclear until after implementation. Agent doesn't know what else to check.

Key Questions:

  • What recent changes had unexpected ripple effects?
  • Which components share data, state, or interfaces?
  • What implicit contracts exist between areas?

Interventions:

  • Document dependency maps
  • Create impact relationship documentation
  • Add "affects" and "affected-by" sections to key nodes

State CN6: Maintenance Failing

Symptoms: Context network was once useful but now drifts from reality. status.md describes old state. Decisions documented but not updated. Agent references outdated information.

Key Questions:

  • When was the network last meaningfully updated?
  • What triggers should cause updates?
  • Who/what is responsible for maintenance?

Interventions:

  • Establish maintenance cadence
  • Define update triggers
  • Integrate with context-retrospective skill for continuous improvement

Operational Modes

Bootstrap Mode (CN0/CN1 → CN2)

Use when starting fresh or organizing scattered documentation.

Process:

1. Existing Documentation Scan

Automatically scan for:

  • README.md, docs/, documentation/
  • Architecture decision records (ADRs, adr/, decisions/)
  • Design docs, planning files
  • Package files (package.json, Cargo.toml, pyproject.toml) for project metadata
  • Existing .claude/ or memory bank structures

Report findings:

Found existing documentation:
- README.md (2.3kb) - Project overview, setup instructions
- docs/architecture.md (5.1kb) - System design
- docs/api.md (3.2kb) - API reference

Recommendation: Migrate architecture.md to context/architecture/,
keep README.md in place as user-facing doc.
2. Project Discovery Questions

Ask:

  • Project type? Software / Research / Creative / Personal Knowledge
  • Primary domains? (For software: frontend, backend, data, infra, etc.)
  • Stakeholders? Solo / Team / Agents / Mixed
  • Expected lifespan? Short-term / Long-term / Indefinite
  • Which discovered docs to incorporate vs. leave in place?
3. Structure Generation

Generate based on project type:

For software projects:

context/
├── status.md           # Current state, active work
├── decisions.md        # Architecture decisions
├── glossary.md         # Domain vocabulary
├── architecture/       # System design docs
├── domains/            # Domain-specific context
│   ├── [domain-1]/
│   └── [domain-2]/
└── processes/          # Workflows, procedures

For research projects:

context/
├── status.md           # Current research state
├── decisions.md        # Methodology decisions
├── glossary.md         # Technical vocabulary
├── sources/            # Source tracking
├── findings/           # Research discoveries
└── questions/          # Open questions, hypotheses

For creative projects:

context/
├── status.md           # Current project state
├── decisions.md        # Creative decisions
├── glossary.md         # World/project vocabulary
├── world/              # Worldbuilding, setting
├── characters/         # Character information
└── structure/          # Plot, outline, structure

For personal knowledge:

context/
├── status.md           # Current focus areas
├── decisions.md        # System decisions
├── glossary.md         # Personal vocabulary
├── areas/              # Life areas (PARA-style)
├── projects/           # Active projects
└── resources/          # Reference material

Also generate:

  • .context-network.md discovery file in project root
  • CLAUDE.md with basic agent instructions (if not present)
4. Migration Execution

For docs user wants to incorporate:

  • Copy/move to appropriate context network location
  • Convert format if needed (e.g., flatten ADRs into decisions.md entries)
  • Update internal cross-references
  • Add relationship metadata
5. Content Coaching

Guide user to populate:

  • status.md: Current state, recent changes, active work
  • decisions.md: Key decisions made, rationale, date
  • glossary.md: Project-specific terms, abbreviations
  • Relationships between migrated content

Maintenance Mode (CN2-CN6 → improved state)

Use when network exists but needs improvement.

Process:

1. State Diagnosis

Analyze:

  • Structure completeness: Required files present? Domains covered?
  • Relationship density: Cross-references per document? Orphan files?
  • Navigation paths: Clear entry points? Task-based routes?
  • Guidance clarity: CLAUDE.md actionable? Instructions followed?
  • Freshness: Last update dates? Stale content?

Produce diagnosis:

Current State: CN3 (Navigation Broken)

Findings:
- 23 context files, 8 with no incoming links (orphans)
- status.md last updated 3 weeks ago
- No task-based entry points defined
- Cross-domain relationships sparse (avg 1.2 per file)

Priority Issues:
1. [Critical] status.md is stale - blocks agent orientation
2. [High] 8 orphan files - content exists but undiscoverable
3. [Medium] Missing hub for API-related context
2. Gap Identification

Prioritize:

  • Critical: Blocking agent effectiveness (can't find what it needs)
  • High: Requires real-time discovery (agent has to search)
  • Medium: Would improve efficiency (extra steps to navigate)
  • Low: Nice-to-have (marginal improvement)
3. Intervention

Based on diagnosed state:

StateGenerateCoach
CN2Relationship templatesHow to identify connections
CN3Hub documents, navigation guidesTask-based organization
CN4CLAUDE.md refinementsWriting actionable instructions
CN5Dependency map templatesImpact analysis process
CN6Maintenance cadence docUpdate triggers, responsibilities

Retrospective Integration

Accept output from context-retrospective skill:

  1. Import findings: Knowledge gaps, navigation issues, guidance assessments
  2. Map to states: Which CN state do these findings indicate?
  3. Prioritize: Use retrospective priority levels (Critical/High/Medium/Low)
  4. Execute: Run appropriate maintenance mode interventions

Anti-Patterns

The Empty Scaffold

Pattern: Generating full directory structure but leaving files empty or with placeholder content only. Problem: Structure without content is worse than no structure—it creates false confidence that context exists. Fix: Generate only structure user commits to populating. Start with status.md and one domain. Expand as content accumulates.

The Kitchen Sink

Pattern: Initial network tries to anticipate every possible need. Complex taxonomies, deep hierarchies, elaborate metadata. Problem: Maintenance burden exceeds value. Network becomes intimidating. Users avoid updating it. Fix: Start minimal. Add structure only when pain emerges from its absence. Two levels of hierarchy maximum initially.

The Orphan Network

Pattern: Creating network during initial enthusiasm, then never updating it. status.md frozen in time. Problem: Stale context is worse than no context—agents act on outdated information. Fix: Establish minimal maintenance triggers: update status.md at session start/end. Schedule periodic retrospectives.

The Template Trap

Pattern: Using templates without adaptation. Every file has same sections regardless of relevance. Problem: Boilerplate obscures actual content. Templates become noise to skip. Fix: Templates are starting points, not requirements. Delete irrelevant sections. Add project-specific ones.

The Completeness Illusion

Pattern: Believing the network can/should capture everything. Adding more and more detail hoping to prevent all gaps. Problem: Signal-to-noise degrades. Navigation becomes impossible. Maintenance unsustainable. Fix: Focus on high-impact gaps. Document what agents actually need. Accept that some discovery will always be real-time.


Verification (Oracle)

What This Skill Can Verify

  • Structure completeness - Required files exist, directories present
  • Link validity - Cross-references point to existing targets
  • Freshness indicators - Last-modified dates, update frequency
  • Orphan detection - Files with no incoming references

What Requires Human Judgment

  • Content quality - Is the information accurate and useful?
  • Relationship accuracy - Do documented connections reflect reality?
  • Appropriate scope - Is the network right-sized for the project?
  • Navigation effectiveness - Do paths match actual usage patterns?

Design Constraints

This Skill Assumes

  • Project benefits from persistent context across sessions
  • User wants agent-accessible documentation
  • Some structure is better than pure freeform notes

This Skill Does Not Handle

  • Real-time project work - Route to: domain-specific skills
  • Retrospective analysis of agent sessions - Route to: context-retrospective
  • Framework development - Route to: skill-builder

Degradation Signals

  • User wants "just a README" - may not need full network
  • Project lifespan < 1 week - overhead may exceed benefit
  • Pure spike/experiment - freeform notes may be better fit

Output Persistence

Output Discovery

Before generating structure:

  1. Check for existing .context-network.md
  2. Check for existing context/ directory
  3. If starting fresh, confirm target location with user

Primary Output

This skill generates:

  • .context-network.md - Discovery file
  • context/ directory structure
  • Template files (status.md, decisions.md, glossary.md)
  • CLAUDE.md updates (if needed)

What Goes Where

Goes to FileStays in Conversation
Directory structureDiagnosis discussion
Template filesCoaching Q&A
Discovery fileMigration decisions
CLAUDE.md updatesPrioritization reasoning

Integration Graph

Inbound (From Other Skills)

Source SkillTriggerAction
context-retrospectiveGap findingsRun Maintenance Mode
skill-builderNew skill needs contextRun Bootstrap Mode

Outbound (To Other Skills)

TriggerTarget SkillReason
Agent behavior problems persist after CN4 interventionReview CLAUDE.md patternsMay need skill-level changes
Network mature, want continuous improvementcontext-retrospectiveRegular health checks

Complementary Skills

SkillRelationship
context-retrospectivePost-hoc analysis feeds maintenance mode
skill-builderSkills may need context network infrastructure

Example Interaction

User: "I'm starting a new TypeScript project and want to set up a context network."

Your approach:

  1. Scan for existing documentation (package.json, README, etc.)
  2. Ask: "What's the primary domain? (e.g., API, CLI, library, full-stack app)"
  3. Generate software-project scaffold based on answer
  4. Create .context-network.md and context/ structure
  5. Coach: "Start with status.md - what's the current state of the project?"

平台分布

Claude Code

26.95%
按下载量换算464

OpenCode

23.3%
按下载量换算401

Antigravity

15.37%
按下载量换算264

Codex

12.86%
按下载量换算221

Cursor

7.04%
按下载量换算121

Gemini CLI

3.65%
按下载量换算63

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。

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