phone-call

安装量: 39
排名: #18323

安装

npx skills add https://github.com/teamily-ai/phone-call-skill --skill phone-call

Phone Call Skill An intelligent AI skill that manages the complete phone call workflow: creating agents, executing calls, analyzing conversations, and providing actionable insights. 🚀 Quick Usage For AI Agents calling this skill:

Single command to make a complete phone call:

scripts/phone_call.sh \ --to "+16576102352" \ --purpose "Make dinner reservation for 2 people tonight at 8 PM. Name: John Smith" What it does: ✅ Creates optimized AI agent ✅ Makes the phone call ✅ Waits for completion ✅ Analyzes conversation ✅ Reports success/failure with recommendations Output: Clear success/failure report with extracted information. Core Capabilities This skill provides complete phone call management : ✅ Agent Creation - Create purpose-specific AI phone agents ✅ Call Execution - Initiate and monitor phone calls ✅ Conversation Analysis - Analyze call transcripts and extract key information ✅ Intelligent Reporting - Provide clear, actionable summaries to users ✅ Continuous Optimization - Learn from failures and improve agent performance When to Use This Skill Use this skill when the user wants to: Make a phone call to someone (restaurant, customer, vendor, etc.) Create an automated phone agent for specific tasks Conduct batch phone calls Have an AI agent communicate via phone Analyze call transcripts and extract insights Get intelligent summaries of phone conversations Quick Start - For AI Agents Simple Usage:

Navigate to skill directory

cd ~/.openclaw/workspace/skills/phone-call

Make a call (automatic agent creation)

./scripts/phone_call.sh \ --to "+1234567890" \ --purpose "Make a dinner reservation for 2 people tonight at 8 PM"

Analyze results

./scripts/phone_call.sh
--analyze
"call-id-xxx"
The script handles everything:
Creates optimized agent based on purpose
Makes the phone call
Waits for completion
Analyzes and reports results
For advanced usage, see "Complete Workflow" below.
Complete Workflow
1. Understand User Intent & Gather Information
When the user requests a phone call, extract and confirm:
Required Information:
Phone number
Target contact (with country code)
Call objective
Specific goal (e.g., "book table for 2 at 8 PM", "confirm meeting")
Key details
All information needed to complete the task
Language
Language preference
Urgency
Time sensitivity
Example User Requests:
"Call +1-657-610-2352 to book a table for 2 people tonight at 8 PM"
"Make a reservation at this restaurant for dinner"
"Call the client to confirm tomorrow's 3 PM meeting"
What YOU Must Do:
Extract ALL required information from the user
Ask for missing details before proceeding
Confirm the complete task objective
2. Create Intelligent Phone Agent
Create an agent optimized for the specific task with proper safeguards.
📚 IMPORTANT: Read
BEST_PRACTICES.md
for detailed guidance on creating effective agents!
The most common failure mode is
identity confusion
- especially for outbound calls. The agent must understand:
WHO is calling WHOM
(YOU are calling THEM for outbound calls)
What NOT to say
(e.g., NEVER say "How can I help you?" on outbound calls)
Specific conversation flow
(not vague objectives)
Agent Configuration Requirements:
Clear objective
Explicit instructions on what to accomplish
Task completion criteria
Agent must know when the task is done
Failure handling
What to do if the task cannot be completed
Timeout settings
Appropriate idle_time and call_duration
Conversation safeguards
"DO NOT hang up until task is confirmed complete"
Key Settings:
{
"prompt"
:
"Clear, step-by-step instructions + completion criteria"
,
"idle_time_seconds"
:
15
,
"endpointing_sensitivity"
:
"relaxed"
,
"ask_if_human_present_on_idle"
:
true
,
"noise_suppression"
:
true
,
"conversation_speed"
:
1.0
}
3. Execute Call & Monitor
Initiate the call and track its progress.
What YOU Must Do:
Make the call using fluents.ai API
Wait for call to complete (don't interrupt mid-call)
Monitor for premature disconnections
Note the call duration and status
Warning Signs to Watch For:
⚠️ Call ends in < 30 seconds (likely failed)
⚠️ No conversation detected
⚠️ Status:
human_disconnected
too quickly
4. Analyze Call Results
CRITICAL: You MUST analyze every call to determine success/failure.
Use the analysis script:
python scripts/analyze_call.py --call-id
"call_xxx"
Required Analysis:
Task Completion Check:
✅ Was the objective achieved? (e.g., reservation confirmed?)
❌ If not, why did it fail?
Conversation Quality:
Did the AI say everything it needed to say?
Did the other party respond?
Was information exchanged properly?
Failure Pattern Detection:
Too short (< 30 seconds) = likely early hangup
One-sided conversation = recognition or response issue
No confirmation = incomplete task execution
Extract Key Information:
Confirmation numbers
Alternative times/dates offered
Reasons for rejection/failure
Any action items
5. Provide Intelligent Report to User
CRITICAL: Always give the user a clear, actionable summary.
Your Report Must Include:
Success Report Format:
✅ Task Completed Successfully!
Reservation Details:
- Restaurant: [Name]
- Date: Tonight
- Time: 8:00 PM
- Party size: 2 people
- Name: John Smith
- Confirmation: [if provided]
Call Duration: 1m 45s
Failure Report Format:
❌ Task Failed - [Reason]
What Happened:
- Call duration: 15 seconds
- Issue: Restaurant hung up immediately
- Transcript: [show what was said]
Root Cause Analysis:
- [Specific problem identified]
Recommended Actions:
1. [Specific next step]
2. [Alternative approach]
3. [When to retry]
📊
Always Include:
Clear success/failure indicator
What was accomplished (or not)
Key information extracted
Next steps or action items
Whether retry is recommended
6. Optimize & Learn
After each call, identify improvements:
If Call Failed:
Analyze WHY it failed
Suggest agent improvements
Recommend retry timing
Consider alternative approaches
If Call Succeeded:
Note what worked well
Can the agent be more efficient?
What patterns led to success?
Common Optimizations:
Adjust idle_time for better patience
Improve prompt clarity
Add noise suppression
Modify conversation speed
Change voice or tone
Add retry logic with delays
Environment Setup
1. Install Dependencies
pip
install
-r
requirements.txt
2. Configure API Keys
Create a
.env
file:
FLUENTS_API_KEY=your_api_key_here
FLUENTS_API_URL=https://api.fluents.ai
WEBHOOK_URL=https://your-webhook.com/callback
3. Test Connection
python scripts/test_connection.py
API Documentation
For detailed fluents.ai API documentation, see:
references/fluents_api.md
- Complete API documentation
references/examples.md
- Usage examples
Security Considerations
Privacy Protection
Ensure you have permission to call the target number
Compliance
Follow local telemarketing and anti-harassment regulations
Key Security
Never commit API keys to version control
Log Management
Properly manage call records with attention to data security Usage Examples Example 1: Simple Call User: "Call 13800138000 to confirm tomorrow's 3 PM meeting" Claude will: Identify the phone call intent Extract information (number: 13800138000, purpose: confirm meeting) Create agent and set conversation script Make the call Wait for call completion Return result: "Called 13800138000, they confirmed attendance at tomorrow's 3 PM meeting" Example 2: Complex Conversation User: "Call the customer to gather product feedback" Claude will: Ask for customer's phone number Create agent with open-ended conversation capabilities Set conversation guidelines (ask about product experience, collect feedback) Make the call and conduct conversation AI analyzes conversation content Provide structured feedback report Troubleshooting Issue: Cannot connect to fluents.ai API Check if API key is correct Verify network connection Check API service status Issue: Call not answered Confirm phone number format is correct (including country code) Check if recipient is in service area Review call logs for details Issue: Speech recognition inaccurate Check if language settings are correct Adjust voice clarity parameters Consider environmental noise factors Technical Support fluents.ai website: https://fluents.ai API documentation: See references/ directory Report issues: Submit a GitHub Issue License MIT License - See LICENSE file for details
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