---

name: coding-agent description: >- Run Codex CLI, Claude Code, or other coding agents as background processes for programmatic control. Use when a user asks to run a coding agent, delegate a task to another AI, spawn a sub-agent, run Claude Code in the background, or orchestrate multiple coding agents on separate tasks. license: Apache-2.0 compatibility: "Requires at least one coding agent CLI installed (claude, codex, etc.)" metadata: author: terminal-skills version: "1.0.0" category: development tags: ["coding-agent", "automation", "sub-agent", "background-process", "orchestration"] use-cases: - "Delegate a well-defined subtask to a background coding agent" - "Run multiple agents in parallel on independent tasks" - "Automate repetitive coding tasks with agent orchestration" agents: [claude-code, openai-codex, gemini-cli, cursor]

Coding Agent

Overview

Run coding agents (Claude Code, Codex CLI, Gemini CLI, or others) as background processes for programmatic task delegation. Spawn sub-agents to handle well-scoped tasks, monitor their progress, and collect results. Useful for parallel task execution, complex multi-step workflows, and automated coding pipelines.

Instructions

When a user asks you to delegate work to a coding agent or run one in the background, follow this process:

Step 1: Verify the agent CLI is available

Check which coding agent CLIs are installed:

# Check for Claude Code
claude --version 2>/dev/null && echo "claude available" || echo "claude not found"

# Check for Codex CLI
codex --version 2>/dev/null && echo "codex available" || echo "codex not found"

# Check for Gemini CLI
gemini --version 2>/dev/null && echo "gemini available" || echo "gemini not found"

If none are available, instruct the user to install one:

# Claude Code
npm install -g @anthropic-ai/claude-code

# Codex CLI
npm install -g @openai/codex

Step 2: Define the task clearly

Before spawning an agent, ensure the task is:

• Well-scoped: A single, clear objective (not "fix everything")
• Self-contained: The agent can complete it without interactive input
• Verifiable: You can check the output or result when done

Write a clear prompt that includes:

• What to do (specific action)
• Where to do it (file paths, directories)
• Constraints (do not modify other files, follow conventions)
• Expected output format

Step 3: Run the agent

Claude Code (background, non-interactive):

# Run with a specific prompt, print-only mode
claude -p "Refactor the function parseConfig in src/config.ts to use zod validation. Do not modify other files." \
  --output-format text \
  2>&1 | tee /tmp/agent-output.txt &

# Store the PID for monitoring
AGENT_PID=$!
echo "Agent running with PID: $AGENT_PID"

Claude Code with specific options:

# Limit scope and disable interactive features
claude -p "Add JSDoc comments to all exported functions in src/utils/" \
  --no-permissions \
  --output-format json \
  > /tmp/agent-result.json 2>&1 &

Codex CLI:

codex --prompt "Write unit tests for src/auth/login.ts covering success, failure, and timeout cases" \
  --auto-approve \
  2>&1 | tee /tmp/codex-output.txt &

Step 4: Monitor and collect results

# Check if the agent is still running
ps -p $AGENT_PID > /dev/null 2>&1 && echo "Still running" || echo "Finished"

# Wait for completion
wait $AGENT_PID
EXIT_CODE=$?
echo "Agent exited with code: $EXIT_CODE"

# Read the output
cat /tmp/agent-output.txt

Step 5: Validate the results

After the agent finishes:

• Check the exit code (0 = success)
• Review the output for errors or warnings
• Verify the changes by reading modified files
• Run any relevant tests to confirm correctness
• Report the results to the user

Examples

Example 1: Delegate test writing to a background agent

User request: "Write tests for the auth module while I work on the API"

Actions:

# Spawn Claude Code to write tests in the background
claude -p "Write comprehensive unit tests for all functions in src/auth/. \
Use vitest as the test framework. Create test files next to source files \
with .test.ts extension. Cover success, failure, and edge cases. \
Do not modify any source files." \
  --output-format text \
  2>&1 | tee /tmp/test-agent.txt &

TEST_PID=$!
echo "Test writing agent started (PID: $TEST_PID)"

After completion, review the generated test files and run the test suite:

wait $TEST_PID
npx vitest run src/auth/

Example 2: Run parallel agents for independent tasks

User request: "Add types to the utils folder and add docs to the components folder"

Actions:

# Agent 1: Add TypeScript types
claude -p "Add strict TypeScript types to all functions in src/utils/. \
Replace any 'any' types with proper types. Do not modify files outside src/utils/." \
  --output-format text > /tmp/types-agent.txt 2>&1 &
PID1=$!

# Agent 2: Add documentation
claude -p "Add JSDoc documentation to all React components in src/components/. \
Include @param, @returns, and @example tags. Do not modify logic." \
  --output-format text > /tmp/docs-agent.txt 2>&1 &
PID2=$!

# Wait for both
wait $PID1 $PID2
echo "Both agents finished"
cat /tmp/types-agent.txt
cat /tmp/docs-agent.txt

Example 3: Agent with structured output

User request: "Analyze the codebase and list all TODO comments with suggested fixes"

Actions:

claude -p "Search the entire src/ directory for TODO, FIXME, and HACK comments. \
For each one, output a JSON array with objects containing: file, line, comment, \
and suggestedFix. Only output the JSON, no other text." \
  --output-format text > /tmp/todos.json 2>&1

# Parse and display
cat /tmp/todos.json | python3 -m json.tool

Guidelines

• Always scope tasks narrowly. Agents work best with focused, well-defined objectives.
• Use --output-format text or --output-format json for programmatic consumption.
• Set reasonable timeouts for background processes to avoid runaway agents.
• Never spawn agents for tasks involving secrets, credentials, or destructive operations.
• Review all agent output before presenting it to the user or applying changes.
• For parallel agents, ensure they work on non-overlapping files to avoid conflicts.
• Capture both stdout and stderr to diagnose failures.
• Prefer spawning one agent per well-defined task over one agent for many tasks.
• If an agent fails, read its output, diagnose the issue, and either retry with a refined prompt or handle the task directly.