Crawler Summary

tiger-learn-anything answer-first brief

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

Claim this agent
Agent DossierGitHubSafety: 94/100

tiger-learn-anything

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

OpenClawself-declared

Public facts

4

Change events

1

Artifacts

0

Freshness

Apr 15, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.

Trust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Apr 15, 2026

Vendor

Tigerkorea

Artifacts

0

Benchmarks

0

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

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.git
  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 2

    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.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Tigerkorea

profilemedium
Observed Apr 15, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Apr 15, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB OPENCLEW

Extracted files

0

Examples

6

Snippets

0

Languages

typescript

Parameters

Executable Examples

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 later

text

[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] Quit

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB OPENCLEW

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

Full README

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] 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

Step 0: Initial Settings

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]

Step 1: Planner

Design a progressive curriculum (easy → hard, concept → practice). Last 1-2 weeks must be integration project + review.

Level rules:

  • Beginner: no formulas, analogies & real-life examples only
  • Intermediate: principles, simple formulas, hands-on code included
  • Advanced: academic papers, official docs, mathematical proofs

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

Step 2-4: Week 1 Generation Only

Generate ONLY week 1 after curriculum approval.

Researcher — collect per week:

  • 4-6 key concepts (5+ sentence definition + 2 examples + analogy each)
  • 4-6 external resources (URL or "Search: {query}" if uncertain)
  • 3-5 key data points (label + value + source)
  • 1 hands-on exercise (title + goal + steps + completion criteria)
  • 5 quiz questions: 2 T/F + 2 short answer + 1 essay

Writer — required sections (in order):

  1. 🗺️ Week Preview — what you'll be able to do after this week
  2. 🧩 Key Concepts — with definition, examples, analogy
  3. 📊 Key Data — table format
  4. 🔗 Recommended Resources — table with type, title, time, description
  5. 🛠️ Hands-on Exercise — goal, steps, completion criteria
  6. Weekly Checklist — actionable checkboxes
  7. Weekly Quiz — 5 questions with collapsible answers
  8. 🚀 Next Week Preview — connection to next week

Word count: minimum 1,500 words

Concept explanation standard:

  • Definition: minimum 5 sentences (background → core → practical meaning)
  • Examples: minimum 2 (good example + bad example OR 2 concrete cases)
  • Analogy: required for EVERY concept

Editor — verify:

  1. All 8 sections present
  2. Word count ≥ 1,500
  3. Level consistency throughout
  4. Quiz: exactly 2 T/F + 2 short + 1 essay
  5. All URLs valid or replaced with search queries

Fix any issues directly, then output final version.


Step 5: Feedback Collection

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:

  1. Update relevant section in SKILL.md
  2. Regenerate week 1 with new rules (overwrite file)
  3. Ask again (max 3 rounds)

If no feedback ("good", "ok", "fine"): → Proceed directly to Step 6


Step 6: Next Action

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎯 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
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

[B] Continue (week by week)

After each week generated:

[{N}/{total}] Week {N} done.
  [Y] Next week  [P] Pause  [Q] Quit

[C] Pause

⏸️  Paused. Files saved at: {output_folder}
To resume: "learn-anything continue" + folder path

Output File Structure

{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)

Completion message:

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎉 Complete! — {topic} {level} {N}-week course
  Estimated reading : ~{N*8} pages
  Recommended study : 3-4 hrs/week
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Resume from Previous Session

When user says "continue", "resume", "from week N", or "이어서":

  1. Ask for output folder path (if not provided)
  2. Use Glob to list existing week files
  3. Generate missing weeks starting from the next one

Notes

  • External links are AI knowledge-based — verify validity yourself
  • Uncertain URLs → use "Search: {query}" format instead
  • All files: UTF-8 encoding
  • If a week fails: log error in week file, continue to next week
  • When updating SKILL.md: modify only the relevant section

Custom Format Rules

This section is auto-updated based on user feedback.

Current rules (defaults):

  • Concept definitions: minimum 5 sentences
  • Examples: minimum 2 per concept (good vs bad)
  • Analogies: required for every concept
  • Word count: minimum 1,500 words per week

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB OPENCLEW

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
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"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

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

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

Self-declaredprotocol-neighbors
GITHUB_REPOSactivepieces

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

OPENCLAW
GITHUB_REPOScherry-studio

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

MCPOPENCLAW
GITHUB_REPOSAionUi

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

MCPOPENCLAW
GITHUB_REPOSCopilotKit

Rank

70

The Frontend for Agents & Generative UI. React + Angular

Traction

No public download signal

Freshness

Updated 23d ago

OPENCLAW
Machine Appendix

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

Ads related to tiger-learn-anything and adjacent AI workflows.