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.
Stars
163
Forks
31
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
bash
# 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
bash
# 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)
bash
# Poll for updates (no processing triggered)
curl http://agent.example.com/news?since=0
Writing to /news (POST)
bash
# 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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