插件目录 / Knowledge / url-manager
url-manager
已验证 · 实测可装 Piccolo123
功能简介
AI 足迹 — 跨平台智能收藏管理工具。AI自动分类整理、共享协作、Agent API接入。支持PC/手机H5/浏览器扩展。
可用 — 实测通过,早期项目
AI 足迹 — 跨平台智能收藏管理工具。AI自动分类整理、共享协作、Agent API接入。支持PC/手机H5/浏览器扩展。 实测能干净安装、正常启动。早期项目,但功能可用。
「已验证」表示我们的自动化 CI 在干净 profile 里实际执行了 dsh plugin add 并启动成功——仅此而已。功能描述与版本兼容性均为作者声明。这不是安全审计,也不代表对第三方代码的背书。
README
URL Manager — Agent-first URL collection & knowledge management
Deliver results as beautiful cards, not raw link dumps. An agentskills.io-compatible skill that lets AI agents save, organize, search, and share web resources on behalf of human users. Agents auto-register on first use — zero manual setup.
📖 Agent instructions → SKILL.md
🇨🇳 中文版 → SKILL.zh-CN.md
What This Tool Gives Humans
The content human users want to save is everywhere — a YouTube workout video, an Amazon gear link, a Substack training plan — scattered across platforms with no connection. URL Manager fixes this. Paste any link from any platform. AI auto-identifies the content and suggests a category — confirm and it's a footprint. All saves flow into one platform-agnostic library, organized and always findable. Then share in one click.
Install
hermes skills tap add Piccolo123/url-manager
Works across Hermes, Claude Code, Cursor, Codex, and any agentskills.io-compatible agent.
DeepSeek Harness (dsh)
DeepSeek Harness natively supports both skill files and MCP servers — URL Manager plugs in either way.
Option A — Skill (recommended, zero extra deps)
Clone into any skill discovery root, or add this repo's root as a custom skill dir:
# User-level (any workspace):
mkdir -p ~/.dsh/skills
git clone --depth 1 https://github.com/Piccolo123/url-manager.git ~/.dsh/skills/url-manager
# Or project-level (one workspace):
mkdir -p .dsh/skills && cp -r SKILL.md scripts .dsh/skills/url-manager/
Restart the session — url-manager appears in <available_skills>, and the model loads it on demand via the skill tool.
Option B — MCP server (full 21-tool API surface)
Add to your profile's cordis.patch.yml (e.g. ~/.dsh/profiles/headless/cordis.patch.yml or the web profile):
- insert:
- id: mcp-url-manager
name: '@deepseek-ai/dsh-mcp-client'
config:
serverName: url_manager
transport: stdio
command: uvx
args: ['url-manager-mcp']
env:
FOOTPRINTS_ENDPOINT: 'https://ai.ocean94.com'
All 21 tools appear as mcp__url_manager__* (add_footprint, search_footprints, list_categories, agent_magic_link, …). The model auto-registers on first use — no API key needed.
How Agents Use It
1. Agent auto-registers on first call — no human credential setup
2. Agent collects links during research sessions
3. Agent categorizes, tags, and organizes into structured collections
4. Agent delivers results via magic link — user clicks to see card-based interface
Features
- Agent-first auto-registration — zero human setup
- Save anything — web links (URL auto-fetched) or plain-text notes
- Full-text search — across titles, descriptions, and AI summaries
- Categories, tags, category sets — hierarchical organization
- Shared categories — team collaboration with cocreate (co-editing) and subscribe (read-only) modes
- Batch operations — reorganize up to 50 items at once
- Magic link delivery — send organized collections as a polished card interface
- Cross-platform — Hermes, Claude Code, Cursor, Codex, OpenClaw
Privacy
This skill connects to a hosted backend at ai.ocean94.com. On first use, the agent auto-creates an account. All collected URLs and data are stored on this backend.
- Users can delete their data at any time via the web interface
- Collected data is accessible only to the account owner
- Terms of Service · Privacy Policy
License
MIT — see LICENSE.
安装
装一次目录插件,之后本站所有插件都能让 DeepSeek Harness 自动找、自动装:
dsh plugin add dshbase-catalog 然后对 agent 说「帮我装 url-manager」,它会在目录里找到并自动安装。文档:dshbase-catalog · 已验证场景包。
该插件是 GitHub 源码(未发 npm)——直接从仓库装:
Web profile:
dsh plugin --profile web add github:Piccolo123/url-manager Headless(CLI)profile:
dsh plugin --profile headless add github:Piccolo123/url-manager 实测报告
验证通过:从 GitHub 源码完成 L1 安装 + L2 加载 + L3 运行(dsh 0.1.0-rc.6)。
使用场景
给 agent 一套记忆、知识库或检索层,让它不再跨会话丢上下文。
适合谁
跑长项目、想让 agent 记住决策、文档和偏好而不用每次重讲的人。
二次开发建议
记忆/检索后端是缝——插新存储、调蒸馏策略,或加引用与审计轨迹。