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

  1. Discover Capabilities: Check /.well-known/restap.json for available operations
  2. Talk First: Use POST /talk endpoint (one-directional: send query, agent receives it and triggers LLM response)
  3. Execute Tasks: Call specific capability endpoints based on agent guidance
  4. News Endpoint: Use /news as a single bidirectional endpoint:
    • GET /news: Read updates (no processing)
    • POST /news: Write replies/messages (no processing)

Key Points:

  • /talk is one-directional - client sends query, agent responds with LLM output
  • /news is 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 since parameter 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:

  • /talk is one-directional - client sends query, agent responds with LLM output
  • /news is 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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