Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
CrowTerminal
Provides persistent, versioned memory and engagement analysis for AI agents supporting creators and influencers across social media platforms.
skill openclawclawhub Free
Provides persistent, versioned memory and engagement analysis for AI agents supporting creators and influencers across social media platforms.
β¬ 0 downloads β
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 2.3.0
Provenance
- Publisher
- WillNigri
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
CrowTerminal - External Brain for AI Agents
"Agents are ephemeral. We are persistent." While your agent stores 10-50 lines of context, CrowTerminal stores 6 months of versioned history for each creator.
What It Does
CrowTerminal is a persistent memory layer for AI agents working with influencers/creators: Versioned Memory - Track what works across sessions (hook patterns, engagement, posting times) Pattern Detection - See trends over months, not single data points Engagement Analysis - Know what configuration performed best historically Validation - Check if your changes will repeat past mistakes Data Ingestion - Push platform data we can't access (retention curves, demographics) LLM-Native API - Schema discovery, semantic field aliases, natural language queries
1. Get API Key (Self-Registration)
curl -X POST "https://api.crowterminal.com/api/agent/register" \ -H "Content-Type: application/json" \ -d '{"agentName": "OpenClaw", "agentDescription": "My personal AI agent"}' Save the returned API key as CROWTERMINAL_API_KEY.
2. Read Creator Memory
curl https://api.crowterminal.com/api/agent/memory/client_123 \ -H "Authorization: Bearer $CROWTERMINAL_API_KEY" Returns versioned skill data: { "version": 47, "skill": { "primaryNiche": "fitness", "hookPatterns": ["confession", "transformation"], "avgEngagement": 4.2, "bestPostingTimes": [{"day": 2, "hour": 7, "score": 0.89}] } }
Schema Discovery (LLM-Friendly)
These endpoints help agents understand what data is available without hardcoding field names: EndpointDescriptionGET /memory/schemaFull schema with field descriptions, types, and semantic aliasesGET /memory/schema/:categorySchema filtered by category (content, performance, timing, audience, history)POST /memory/resolveResolve natural language queries to field names Example: Discover available fields curl https://api.crowterminal.com/api/agent/memory/schema \ -H "Authorization: Bearer $CROWTERMINAL_API_KEY" Returns field definitions with semantic aliases: { "fields": { "avgEngagement": { "type": "number", "description": "Average engagement rate", "aliases": ["engagement", "engagement rate", "interaction rate"], "category": "performance" } } }
Smart Query (Natural Language)
Query data using natural language instead of exact field names: EndpointDescriptionPOST /memory/:clientId/queryQuery with natural language ("engagement and hooks")GET /memory/:clientId/overviewHuman-readable summary of the creatorGET /memory/:clientId/changesNatural language summary of recent changesGET /memory/:clientId/insightsAI-friendly performance insights Example: Natural language query curl -X POST "https://api.crowterminal.com/api/agent/memory/client_123/query" \ -H "Authorization: Bearer $CROWTERMINAL_API_KEY" \ -H "Content-Type: application/json" \ -d '{"query": "engagement and hooks"}' Returns matched data: { "results": { "matchedFields": ["avgEngagement", "hookPatterns"], "data": { "avgEngagement": 4.2, "hookPatterns": ["confession", "POV"] }, "context": "avgEngagement: Average engagement rate; hookPatterns: Effective hook types" } } Example: Get natural language overview curl https://api.crowterminal.com/api/agent/memory/client_123/overview \ -H "Authorization: Bearer $CROWTERMINAL_API_KEY" Returns: { "overview": "FitnessGuru is a fitness creator averaging 125,000 views per video with 4.2% engagement and is currently growing. Their best-performing hooks are: confession, transformation, POV." }
Memory Layer (Core)
EndpointDescriptionGET /memory/:clientIdCurrent skill versionGET /memory/:clientId/versionsVersion historyGET /memory/:clientId/diff?from=5&to=10Compare versionsGET /memory/:clientId/pattern?field=engagementTrack field over time with trend analysisPOST /memory/:clientId/validateCheck before changingPOST /memory/:clientId/engagement-analysisTHE KILLER ENDPOINT
The Killer Endpoint: Engagement Analysis
Send your current learnings, get back what configuration performed best: curl -X POST "https://api.crowterminal.com/api/agent/memory/client_123/engagement-analysis" \ -H "Authorization: Bearer $CROWTERMINAL_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "agentMd": { "hookPatterns": ["confession"], "contentStyle": "casual" } }' Returns: { "overallStats": { "peakEngagement": 6.2, "yourSimilarityToTop": "65%" }, "recommendations": [ "Change hookPatterns to [\"POV\",\"confession\"] (+51% potential)" ] }
Data Ingestion (Push Your Data)
Push platform data we can't access via API: curl -X POST "https://api.crowterminal.com/api/agent/data/ingest" \ -H "Authorization: Bearer $CROWTERMINAL_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "clientId": "client_123", "platform": "TIKTOK", "dataType": "retention", "data": { "retentionCurve": [100, 95, 88, 75, 60, 45, 30], "avgWatchTime": 12.5 } }'
Webhooks (Async Notifications)
curl -X POST "https://api.crowterminal.com/api/agent/webhooks" \ -H "Authorization: Bearer $CROWTERMINAL_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "url": "https://your-server.com/webhook", "events": ["skill.updated", "data.ingested"] }'
Service Status (No Auth)
curl https://api.crowterminal.com/api/agent/status
Sandbox (Test Without Auth)
Test endpoints without affecting real data: Memory & Schema: GET /api/agent/sandbox/client - Mock client data GET /api/agent/sandbox/memory - Mock memory/skill GET /api/agent/sandbox/schema - Schema discovery POST /api/agent/sandbox/resolve - Resolve field aliases Smart Query: POST /api/agent/sandbox/query - Natural language queries GET /api/agent/sandbox/overview - Creator overview GET /api/agent/sandbox/changes - Recent changes summary GET /api/agent/sandbox/insights - Performance insights Analysis: POST /api/agent/sandbox/validate - Validate changes POST /api/agent/sandbox/engagement-analysis - Engagement analysis POST /api/agent/sandbox/ingest - Data ingestion
Why Use CrowTerminal?
Your agent learns β forgets β relearns - We remember One bad video β pattern change - We track across versions Data you can't get via API - We accept it via ingestion BYOK - Use your own LLM, we just provide context LLM-Native - No hardcoding field names, use natural language queries Self-Documenting - Schema endpoint tells you what data exists
Pricing
FREE during beta. We want agents to test and give feedback. TierPriceMemory Read/WriteFREEData IngestionFREEBYOK (your LLM)FREEFull ServiceFREE
Documentation
Full Docs: https://crowterminal.com/llms.txt MCP Manifest: https://crowterminal.com/.well-known/mcp.json OpenAPI: https://api.crowterminal.com/api/docs.json SDKs: Python (pip install crowterminal), TypeScript (npm install crowterminal)
Support
Email: agents@crowterminal.com GitHub: https://github.com/WillNigri/FluxOps "Your agent's external hard drive. Because context windows aren't long-term memory."
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs
- SKILL.md