Agent skill
text-agent-client
Interact with the Text Processing AI Agent. Use when you need text analysis, formatting, or processing capabilities from the agent.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/development/text-agent-client
SKILL.md
Text Processing Agent Client Skill
Overview
This skill teaches how to effectively interact with the Text Processing AI Agent's REST-AP endpoints for various text operations.
When to Use This Skill
- Need text analysis or processing
- Want to format or transform text content
- Require document processing capabilities
- Need content validation or cleaning
Agent Interaction Patterns
Basic Text Operations
# Echo text through the agent
curl -X POST http://agent.example.com/text/echo \
-H "Content-Type: application/json" \
-d '{"text": "Hello World"}'
Conversational Interaction
# Talk to the agent (one-directional: send query, receive LLM response)
curl -X POST http://agent.example.com/talk \
-H "Content-Type: application/json" \
-d '{"message": "How can you help with text processing?"}'
Agent Communication Workflow
- Discover Capabilities: Check /.well-known/restap.json for available operations
- Talk First: Use POST /talk endpoint (one-directional: send query, agent receives it and triggers LLM response)
- Execute Tasks: Call specific capability endpoints based on agent guidance
- News Endpoint: Use /news as a single bidirectional endpoint:
- GET /news: Read updates (no processing)
- POST /news: Write replies/messages (no processing)
Key Points:
/talkis one-directional - client sends query, agent responds with LLM output/newsis bidirectional - can read (GET) and write (POST), but never triggers agent processing
Best Practices
- Always check agent capabilities before making requests
- Use the /talk endpoint to understand proper usage patterns
- Handle both successful responses and error cases
- Respect rate limits and implement appropriate backoff
- Validate response formats before processing
Common Interaction Patterns
- Start with capability discovery via /.well-known/restap.json
- Use /talk for complex requests or when unsure of proper usage
- Implement proper error handling for network issues
- Poll GET /news for asynchronous operation completion
- Use POST /news to send replies directly to other agents (prevents loops)
- Use
sinceparameter when polling: GET /news?since=timestamp - Cache agent capabilities to reduce discovery overhead
The /news Endpoint: Single Entrypoint for Reading and Writing
The /news endpoint is a single bidirectional entrypoint that handles both reading and writing. The critical property: it never triggers agent processing.
Reading from /news (GET)
# Poll for updates (no processing triggered)
curl http://agent.example.com/news?since=0
Writing to /news (POST)
# Send reply to another agent (no processing triggered)
curl -X POST http://agent-a.example.com/news \
-H "Content-Type: application/json" \
-d '{
"type": "reply",
"from": "agent-b",
"in_reply_to": "query_123",
"message": "Here is my response..."
}'
Complete Flow Example
Agent 1 → POST /talk → Agent 2 (one-directional: Agent 2 receives query, triggers LLM response)
Agent 2 → POST /news → Agent 1 (bidirectional write: just stored, no processing)
Agent 3 → GET /news → Agent 2 (bidirectional read: just reads, no processing)
Why this matters:
/talkis one-directional - client sends query, agent responds with LLM output/newsis bidirectional but never triggers processing - prevents infinite loops- When you send a reply via
POST /news, the receiving agent doesn't process it - it's just stored - This allows safe bidirectional communication without triggering endless processing cycles
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