Rank
83
A Model Context Protocol (MCP) server for GitLab
Traction
No public download signal
Freshness
Updated 2d ago
Crawler Summary
AI 领域系统学习体系。管理知识图谱、深度学习笔记、实战复盘和关联网络。触发场景:学习计划、知识图谱更新、深度研究某个 AI 主题、实战复盘总结、调研后沉淀知识、每周学习回顾。当用户说'学了什么'、'总结一下'、'沉淀知识'、'复盘'、'更新图谱'、'深入研究'、'写笔记'、'学习回顾'、'review what I learned'、'update knowledge map'、'deep dive'、'recap'、'what did I learn' 时使用。当改完代码/读完论文/做完调研后需要提炼和归纳时使用。 --- name: learning-system description: "AI 领域系统学习体系。管理知识图谱、深度学习笔记、实战复盘和关联网络。触发场景:学习计划、知识图谱更新、深度研究某个 AI 主题、实战复盘总结、调研后沉淀知识、每周学习回顾。当用户说'学了什么'、'总结一下'、'沉淀知识'、'复盘'、'更新图谱'、'深入研究'、'写笔记'、'学习回顾'、'review what I learned'、'update knowledge map'、'deep dive'、'recap'、'what did I learn' 时使用。当改完代码/读完论文/做完调研后需要提炼和归纳时使用。" argument-hint: "[--mode deep-dive|recap|review|health] [--topic name] [--quick]" --- Learning System 将零散的资讯、调研、代码实战转 Capability contract not published. No trust telemetry is available yet. 4 GitHub stars reported by the source. Last updated 4/15/2026.
Freshness
Last checked 4/15/2026
Best For
learning-system is best for general automation workflows where MCP and OpenClaw compatibility matters.
Not Ideal For
Contract metadata is missing or unavailable for deterministic execution.
Evidence Sources Checked
editorial-content, GITHUB OPENCLEW, runtime-metrics, public facts pack
AI 领域系统学习体系。管理知识图谱、深度学习笔记、实战复盘和关联网络。触发场景:学习计划、知识图谱更新、深度研究某个 AI 主题、实战复盘总结、调研后沉淀知识、每周学习回顾。当用户说'学了什么'、'总结一下'、'沉淀知识'、'复盘'、'更新图谱'、'深入研究'、'写笔记'、'学习回顾'、'review what I learned'、'update knowledge map'、'deep dive'、'recap'、'what did I learn' 时使用。当改完代码/读完论文/做完调研后需要提炼和归纳时使用。 --- name: learning-system description: "AI 领域系统学习体系。管理知识图谱、深度学习笔记、实战复盘和关联网络。触发场景:学习计划、知识图谱更新、深度研究某个 AI 主题、实战复盘总结、调研后沉淀知识、每周学习回顾。当用户说'学了什么'、'总结一下'、'沉淀知识'、'复盘'、'更新图谱'、'深入研究'、'写笔记'、'学习回顾'、'review what I learned'、'update knowledge map'、'deep dive'、'recap'、'what did I learn' 时使用。当改完代码/读完论文/做完调研后需要提炼和归纳时使用。" argument-hint: "[--mode deep-dive|recap|review|health] [--topic name] [--quick]" --- Learning System 将零散的资讯、调研、代码实战转
Public facts
5
Change events
1
Artifacts
0
Freshness
Apr 15, 2026
Capability contract not published. No trust telemetry is available yet. 4 GitHub stars reported by the source. Last updated 4/15/2026.
Trust score
Unknown
Compatibility
MCP, OpenClaw
Freshness
Apr 15, 2026
Vendor
Echovic
Artifacts
0
Benchmarks
0
Last release
Unpublished
Key links, install path, and a quick operational read before the deeper crawl record.
Summary
Capability contract not published. No trust telemetry is available yet. 4 GitHub stars reported by the source. Last updated 4/15/2026.
Setup snapshot
git clone https://github.com/echoVic/learning-system-skill.gitSetup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.
Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.
Vendor
Echovic
Protocol compatibility
MCP, OpenClaw
Adoption signal
4 GitHub stars
Handshake status
UNKNOWN
Crawlable docs
6 indexed pages on the official domain
Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.
Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.
Extracted files
0
Examples
3
Snippets
0
Languages
typescript
Parameters
text
notes/areas/
├── ai-knowledge-map.md # 知识图谱(掌握程度标记)
├── deep-dives/ # 深度学习笔记
│ ├── mcp-tool-call-design.md
│ └── ...
└── weekly-reviews/ # 每周学习回顾
├── 2026-W07.md
└── ...bash
python3 scripts/health_check.py
bash
python3 scripts/mastery_score.py # 表格报告 python3 scripts/mastery_score.py --json # 附加 JSON 输出
Full documentation captured from public sources, including the complete README when available.
Docs source
GITHUB OPENCLEW
Editorial quality
ready
AI 领域系统学习体系。管理知识图谱、深度学习笔记、实战复盘和关联网络。触发场景:学习计划、知识图谱更新、深度研究某个 AI 主题、实战复盘总结、调研后沉淀知识、每周学习回顾。当用户说'学了什么'、'总结一下'、'沉淀知识'、'复盘'、'更新图谱'、'深入研究'、'写笔记'、'学习回顾'、'review what I learned'、'update knowledge map'、'deep dive'、'recap'、'what did I learn' 时使用。当改完代码/读完论文/做完调研后需要提炼和归纳时使用。 --- name: learning-system description: "AI 领域系统学习体系。管理知识图谱、深度学习笔记、实战复盘和关联网络。触发场景:学习计划、知识图谱更新、深度研究某个 AI 主题、实战复盘总结、调研后沉淀知识、每周学习回顾。当用户说'学了什么'、'总结一下'、'沉淀知识'、'复盘'、'更新图谱'、'深入研究'、'写笔记'、'学习回顾'、'review what I learned'、'update knowledge map'、'deep dive'、'recap'、'what did I learn' 时使用。当改完代码/读完论文/做完调研后需要提炼和归纳时使用。" argument-hint: "[--mode deep-dive|recap|review|health] [--topic name] [--quick]" --- Learning System 将零散的资讯、调研、代码实战转
将零散的资讯、调研、代码实战转化为体系化的 AI 领域专业知识。
输入不等于学习。 看了 100 篇推文不代表懂了推理优化。改了 3 个 MCP bug 不代表吃透了 MCP 协议。学习 = 输入 + 加工 + 关联 + 输出。
根据 $ARGUMENTS 或用户意图选择模式:
| 参数 | 模式 | 说明 |
|------|------|------|
| --mode deep-dive | 深度研究 | 选题 → 研究 → 写笔记 → 更新图谱 |
| --mode recap | 实战复盘 | 分析 PR/改动 → 提炼知识点 → 关联图谱 |
| --mode review | 每周回顾 | 汇总本周 → 更新图谱 → 生成周报 |
| --mode health | 健康检查 | 运行 scripts/health_check.py 输出报告 |
| 无参数 | 自动判断 | 根据上下文推断最合适的模式 |
附加参数:
--topic <name>: 指定主题(deep-dive 模式)--quick: 跳过确认节点,全自动执行notes/areas/
├── ai-knowledge-map.md # 知识图谱(掌握程度标记)
├── deep-dives/ # 深度学习笔记
│ ├── mcp-tool-call-design.md
│ └── ...
└── weekly-reviews/ # 每周学习回顾
├── 2026-W07.md
└── ...
Copy this checklist and check off items as you complete them:
--topic 已指定,直接使用--quick)
references/deep-dive-template.md 获取笔记模板notes/areas/deep-dives/ 创建笔记文件→ 关联: [主题](相对路径)references/knowledge-map-rules.md 获取升级标准notes/areas/ai-knowledge-map.md 中对应主题的掌握程度references/quality-checklist.md 逐项验证references/recap-template.md 获取复盘模板memory/YYYY-MM-DD.md 中增加复盘 sectionreferences/knowledge-map-rules.md 并更新references/knowledge-map-rules.md--quick)notes/areas/ai-knowledge-map.mdreferences/weekly-review-template.mdnotes/areas/weekly-reviews/2026-Wxx.mdpython3 scripts/health_check.py
输出知识图谱统计、深度笔记状态、本周活动量、改进建议。
python3 scripts/mastery_score.py # 表格报告
python3 scripts/mastery_score.py --json # 附加 JSON 输出
自动计算每个知识图谱主题的掌握分数,基于:
输出包含:分数排名、建议升降级、衰减警告(60 天未接触)。
在深度笔记和复盘中主动建立关联。格式:→ 关联: [主题](相对路径)
| 关联类型 | 示例 | |----------|------| | 技术关联 | vLLM → PagedAttention → KV Cache 管理 | | 实战关联 | gemini-cli OAuth PR → OAuth 2.1 协议 | | 对比关联 | Flash Attention vs PagedAttention |
Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.
Contract coverage
Status
missing
Auth
None
Streaming
No
Data region
Unspecified
Protocol support
Requires: none
Forbidden: none
Guardrails
Operational confidence: low
curl -s "https://xpersona.co/api/v1/agents/echovic-learning-system-skill/snapshot"
curl -s "https://xpersona.co/api/v1/agents/echovic-learning-system-skill/contract"
curl -s "https://xpersona.co/api/v1/agents/echovic-learning-system-skill/trust"
Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.
Trust signals
Handshake
UNKNOWN
Confidence
unknown
Attempts 30d
unknown
Fallback rate
unknown
Runtime metrics
Observed P50
unknown
Observed P95
unknown
Rate limit
unknown
Estimated cost
unknown
Do not use if
Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.
Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.
Rank
83
A Model Context Protocol (MCP) server for GitLab
Traction
No public download signal
Freshness
Updated 2d ago
Rank
80
A Model Context Protocol (MCP) server for GitLab
Traction
No public download signal
Freshness
Updated 2d ago
Rank
74
Expose OpenAPI definition endpoints as MCP tools using the official Rust SDK for the Model Context Protocol (https://github.com/modelcontextprotocol/rust-sdk)
Traction
No public download signal
Freshness
Updated 2d ago
Rank
72
An actix_web backend for the official Rust SDK for the Model Context Protocol (https://github.com/modelcontextprotocol/rust-sdk)
Traction
No public download signal
Freshness
Updated 2d ago
Contract JSON
{
"contractStatus": "missing",
"authModes": [],
"requires": [],
"forbidden": [],
"supportsMcp": false,
"supportsA2a": false,
"supportsStreaming": false,
"inputSchemaRef": null,
"outputSchemaRef": null,
"dataRegion": null,
"contractUpdatedAt": null,
"sourceUpdatedAt": null,
"freshnessSeconds": null
}Invocation Guide
{
"preferredApi": {
"snapshotUrl": "https://xpersona.co/api/v1/agents/echovic-learning-system-skill/snapshot",
"contractUrl": "https://xpersona.co/api/v1/agents/echovic-learning-system-skill/contract",
"trustUrl": "https://xpersona.co/api/v1/agents/echovic-learning-system-skill/trust"
},
"curlExamples": [
"curl -s \"https://xpersona.co/api/v1/agents/echovic-learning-system-skill/snapshot\"",
"curl -s \"https://xpersona.co/api/v1/agents/echovic-learning-system-skill/contract\"",
"curl -s \"https://xpersona.co/api/v1/agents/echovic-learning-system-skill/trust\""
],
"jsonRequestTemplate": {
"query": "summarize this repo",
"constraints": {
"maxLatencyMs": 2000,
"protocolPreference": [
"MCP",
"OPENCLEW"
]
}
},
"jsonResponseTemplate": {
"ok": true,
"result": {
"summary": "...",
"confidence": 0.9
},
"meta": {
"source": "GITHUB_OPENCLEW",
"generatedAt": "2026-04-17T00:22:29.455Z"
}
},
"retryPolicy": {
"maxAttempts": 3,
"backoffMs": [
500,
1500,
3500
],
"retryableConditions": [
"HTTP_429",
"HTTP_503",
"NETWORK_TIMEOUT"
]
}
}Trust JSON
{
"status": "unavailable",
"handshakeStatus": "UNKNOWN",
"verificationFreshnessHours": null,
"reputationScore": null,
"p95LatencyMs": null,
"successRate30d": null,
"fallbackRate": null,
"attempts30d": null,
"trustUpdatedAt": null,
"trustConfidence": "unknown",
"sourceUpdatedAt": null,
"freshnessSeconds": null
}Capability Matrix
{
"rows": [
{
"key": "MCP",
"type": "protocol",
"support": "unknown",
"confidenceSource": "profile",
"notes": "Listed on profile"
},
{
"key": "OPENCLEW",
"type": "protocol",
"support": "unknown",
"confidenceSource": "profile",
"notes": "Listed on profile"
}
],
"flattenedTokens": "protocol:MCP|unknown|profile protocol:OPENCLEW|unknown|profile"
}Facts JSON
[
{
"factKey": "docs_crawl",
"category": "integration",
"label": "Crawlable docs",
"value": "6 indexed pages on the official domain",
"href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceType": "search_document",
"confidence": "medium",
"observedAt": "2026-04-15T05:03:46.393Z",
"isPublic": true
},
{
"factKey": "vendor",
"category": "vendor",
"label": "Vendor",
"value": "Echovic",
"href": "https://github.com/echoVic/learning-system-skill",
"sourceUrl": "https://github.com/echoVic/learning-system-skill",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-04-15T01:15:43.419Z",
"isPublic": true
},
{
"factKey": "protocols",
"category": "compatibility",
"label": "Protocol compatibility",
"value": "MCP, OpenClaw",
"href": "https://xpersona.co/api/v1/agents/echovic-learning-system-skill/contract",
"sourceUrl": "https://xpersona.co/api/v1/agents/echovic-learning-system-skill/contract",
"sourceType": "contract",
"confidence": "medium",
"observedAt": "2026-04-15T01:15:43.419Z",
"isPublic": true
},
{
"factKey": "traction",
"category": "adoption",
"label": "Adoption signal",
"value": "4 GitHub stars",
"href": "https://github.com/echoVic/learning-system-skill",
"sourceUrl": "https://github.com/echoVic/learning-system-skill",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-04-15T01:15:43.419Z",
"isPublic": true
},
{
"factKey": "handshake_status",
"category": "security",
"label": "Handshake status",
"value": "UNKNOWN",
"href": "https://xpersona.co/api/v1/agents/echovic-learning-system-skill/trust",
"sourceUrl": "https://xpersona.co/api/v1/agents/echovic-learning-system-skill/trust",
"sourceType": "trust",
"confidence": "medium",
"observedAt": null,
"isPublic": true
}
]Change Events JSON
[
{
"eventType": "docs_update",
"title": "Docs refreshed: Sign in to GitHub · GitHub",
"description": "Fresh crawlable documentation was indexed for the official domain.",
"href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceType": "search_document",
"confidence": "medium",
"observedAt": "2026-04-15T05:03:46.393Z",
"isPublic": true
}
]Sponsored
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