Rank
70
AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
Traction
No public download signal
Freshness
Updated 2d ago
Crawler Summary
Learn-Anything — AI Curriculum Generator --- name: learn-anything description: Generate structured learning curriculum for any topic using a 4-agent AI pipeline. Triggers: "learn anything", "learn-anything", "커리큘럼만들어", "학습커리큘럼", "호랑이 런애니띵", "런애니씽", "런애니띵" --- Learn-Anything — AI Curriculum Generator Any topic → Settings → Curriculum → Week 1 → Feedback → Continue --- Workflow --- Step 0: Initial Settings Ask for missing items in order. Skip if already provi Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.
Freshness
Last checked 4/15/2026
Best For
tiger-learn-anything is best for general automation workflows where 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
Learn-Anything — AI Curriculum Generator --- name: learn-anything description: Generate structured learning curriculum for any topic using a 4-agent AI pipeline. Triggers: "learn anything", "learn-anything", "커리큘럼만들어", "학습커리큘럼", "호랑이 런애니띵", "런애니씽", "런애니띵" --- Learn-Anything — AI Curriculum Generator Any topic → Settings → Curriculum → Week 1 → Feedback → Continue --- Workflow --- Step 0: Initial Settings Ask for missing items in order. Skip if already provi
Public facts
4
Change events
1
Artifacts
0
Freshness
Apr 15, 2026
Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.
Trust score
Unknown
Compatibility
OpenClaw
Freshness
Apr 15, 2026
Vendor
Tigerkorea
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Unpublished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. Last updated 4/15/2026.
Setup snapshot
git clone https://github.com/tigerkorea/tiger-learn-anything.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
Tigerkorea
Protocol compatibility
OpenClaw
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
6
Snippets
0
Languages
typescript
Parameters
text
[Step 0] Settings (topic / level / weeks / model / output folder)
↓
[Step 1: Planner] Design curriculum → User approval
↓
[Step 2-4: Week 1 only] Researcher → Writer → Editor → Save
↓
[Step 5: Feedback] Update SKILL.md if changes requested
↓
[Step 6: Branch]
[A] Restart — regenerate from week 1 with new format
[B] Continue — generate week 2+ one by one
[C] Pause — resume latertext
[1] Beginner — concepts only, no formulas [2] Intermediate — principles + hands-on ← recommended [3] Advanced — papers, deep technical analysis
text
[1] 4 weeks — compact essentials [2] 8 weeks — balanced ← recommended [3] 12 weeks — comprehensive
text
[1] claude-sonnet-4-6 — fast, cost-efficient ← recommended [2] claude-opus-4-6 — highest quality, slower
text
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚙️ Settings Confirmed
Topic : {topic}
Level : {level}
Duration: {N} weeks
Model : {model}
Output : {output_folder}/{slug}_{level}_{N}w_{date}/
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Proceed? [Y/N]text
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📋 Curriculum Draft — {topic} ({level}, {N} weeks)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Overview: {2-3 sentences on what you'll achieve}
Week 1: {title}
{subtitle — the key question this week}
▸ Concepts: {c1}, {c2}, {c3}...
▸ Practice: {goal}
▸ Deliverable: {item}
...
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Happy with this curriculum?
[Y] Approve — start generating week 1
[R] Regenerate (max 3 times)
[Q] QuitFull documentation captured from public sources, including the complete README when available.
Docs source
GITHUB OPENCLEW
Editorial quality
ready
Learn-Anything — AI Curriculum Generator --- name: learn-anything description: Generate structured learning curriculum for any topic using a 4-agent AI pipeline. Triggers: "learn anything", "learn-anything", "커리큘럼만들어", "학습커리큘럼", "호랑이 런애니띵", "런애니씽", "런애니띵" --- Learn-Anything — AI Curriculum Generator Any topic → Settings → Curriculum → Week 1 → Feedback → Continue --- Workflow --- Step 0: Initial Settings Ask for missing items in order. Skip if already provi
Any topic → Settings → Curriculum → Week 1 → Feedback → Continue
[Step 0] Settings (topic / level / weeks / model / output folder)
↓
[Step 1: Planner] Design curriculum → User approval
↓
[Step 2-4: Week 1 only] Researcher → Writer → Editor → Save
↓
[Step 5: Feedback] Update SKILL.md if changes requested
↓
[Step 6: Branch]
[A] Restart — regenerate from week 1 with new format
[B] Continue — generate week 2+ one by one
[C] Pause — resume later
Ask for missing items in order. Skip if already provided as arguments.
Topic: "What topic would you like to study?"
Level:
[1] Beginner — concepts only, no formulas
[2] Intermediate — principles + hands-on ← recommended
[3] Advanced — papers, deep technical analysis
Duration:
[1] 4 weeks — compact essentials
[2] 8 weeks — balanced ← recommended
[3] 12 weeks — comprehensive
Model:
[1] claude-sonnet-4-6 — fast, cost-efficient ← recommended
[2] claude-opus-4-6 — highest quality, slower
Output folder: Default {cwd}/learn-output/
Confirm display:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚙️ Settings Confirmed
Topic : {topic}
Level : {level}
Duration: {N} weeks
Model : {model}
Output : {output_folder}/{slug}_{level}_{N}w_{date}/
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Proceed? [Y/N]
Design a progressive curriculum (easy → hard, concept → practice). Last 1-2 weeks must be integration project + review.
Level rules:
Display format:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📋 Curriculum Draft — {topic} ({level}, {N} weeks)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Overview: {2-3 sentences on what you'll achieve}
Week 1: {title}
{subtitle — the key question this week}
▸ Concepts: {c1}, {c2}, {c3}...
▸ Practice: {goal}
▸ Deliverable: {item}
...
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Happy with this curriculum?
[Y] Approve — start generating week 1
[R] Regenerate (max 3 times)
[Q] Quit
Generate ONLY week 1 after curriculum approval.
Word count: minimum 1,500 words
Concept explanation standard:
Fix any issues directly, then output final version.
After saving week 1 file:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✅ Week 1 complete!
📁 Saved: {file_path}
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
How does this format look?
Tell me what to change, or say "good"/"ok" to continue.
If feedback received:
If no feedback ("good", "ok", "fine"): → Proceed directly to Step 6
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎯 What would you like to do next?
[A] Restart — regenerate all weeks with updated format
[B] Continue — generate week 2 onwards (one at a time)
[C] Pause — I'll continue later
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
After each week generated:
[{N}/{total}] Week {N} done.
[Y] Next week [P] Pause [Q] Quit
⏸️ Paused. Files saved at: {output_folder}
To resume: "learn-anything continue" + folder path
{output_folder}/{topic_slug}_{level}_{N}w_{YYYYMMDD}/
├── 00_curriculum.md ← full curriculum + settings header
├── week01.md ← week 1 (post-feedback final version)
├── week02.md
├── ...
└── full_course.md ← combined (generated after ALL weeks done)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎉 Complete! — {topic} {level} {N}-week course
Estimated reading : ~{N*8} pages
Recommended study : 3-4 hrs/week
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
When user says "continue", "resume", "from week N", or "이어서":
This section is auto-updated based on user feedback.
Current rules (defaults):
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/tigerkorea-tiger-learn-anything/snapshot"
curl -s "https://xpersona.co/api/v1/agents/tigerkorea-tiger-learn-anything/contract"
curl -s "https://xpersona.co/api/v1/agents/tigerkorea-tiger-learn-anything/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
70
AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
Traction
No public download signal
Freshness
Updated 2d ago
Rank
70
AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs
Traction
No public download signal
Freshness
Updated 5d ago
Rank
70
Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!
Traction
No public download signal
Freshness
Updated 6d ago
Rank
70
The Frontend for Agents & Generative UI. React + Angular
Traction
No public download signal
Freshness
Updated 23d 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/tigerkorea-tiger-learn-anything/snapshot",
"contractUrl": "https://xpersona.co/api/v1/agents/tigerkorea-tiger-learn-anything/contract",
"trustUrl": "https://xpersona.co/api/v1/agents/tigerkorea-tiger-learn-anything/trust"
},
"curlExamples": [
"curl -s \"https://xpersona.co/api/v1/agents/tigerkorea-tiger-learn-anything/snapshot\"",
"curl -s \"https://xpersona.co/api/v1/agents/tigerkorea-tiger-learn-anything/contract\"",
"curl -s \"https://xpersona.co/api/v1/agents/tigerkorea-tiger-learn-anything/trust\""
],
"jsonRequestTemplate": {
"query": "summarize this repo",
"constraints": {
"maxLatencyMs": 2000,
"protocolPreference": [
"OPENCLEW"
]
}
},
"jsonResponseTemplate": {
"ok": true,
"result": {
"summary": "...",
"confidence": 0.9
},
"meta": {
"source": "GITHUB_OPENCLEW",
"generatedAt": "2026-04-17T02:07:37.028Z"
}
},
"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": "OPENCLEW",
"type": "protocol",
"support": "unknown",
"confidenceSource": "profile",
"notes": "Listed on profile"
}
],
"flattenedTokens": "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": "Tigerkorea",
"href": "https://github.com/tigerkorea/tiger-learn-anything",
"sourceUrl": "https://github.com/tigerkorea/tiger-learn-anything",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-04-15T01:14:11.443Z",
"isPublic": true
},
{
"factKey": "protocols",
"category": "compatibility",
"label": "Protocol compatibility",
"value": "OpenClaw",
"href": "https://xpersona.co/api/v1/agents/tigerkorea-tiger-learn-anything/contract",
"sourceUrl": "https://xpersona.co/api/v1/agents/tigerkorea-tiger-learn-anything/contract",
"sourceType": "contract",
"confidence": "medium",
"observedAt": "2026-04-15T01:14:11.443Z",
"isPublic": true
},
{
"factKey": "handshake_status",
"category": "security",
"label": "Handshake status",
"value": "UNKNOWN",
"href": "https://xpersona.co/api/v1/agents/tigerkorea-tiger-learn-anything/trust",
"sourceUrl": "https://xpersona.co/api/v1/agents/tigerkorea-tiger-learn-anything/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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