paseo

Use when entering orchestrator mode to manage agents via Paseo CLI

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Install skill "paseo" with this command: npx skills add getpaseo/paseo/getpaseo-paseo-paseo

Paseo CLI Commands

Use these CLI commands to manage agents:

# List agents (directory-scoped by default)
paseo ls                 # Only shows agents for current directory
paseo ls -g              # All agents across all projects (global)
paseo ls --json          # JSON output for parsing

# Create and run an agent (blocks until completion by default, no timeout)
paseo run --mode bypass "<prompt>"
paseo run --mode bypass --name "Task Name" "<prompt>"
paseo run --mode bypass --model opus "<prompt>"
paseo run --mode full-access --provider codex "<prompt>"

# Wait timeout - limit how long run blocks (default: no limit)
paseo run --wait-timeout 30m "<prompt>"   # Wait up to 30 minutes
paseo run --wait-timeout 1h "<prompt>"    # Wait up to 1 hour
paseo run --wait-timeout 3600 "<prompt>"  # Plain number = seconds

# Detached mode - runs in background, returns agent ID immediately
paseo run --detach "<prompt>"
paseo run -d "<prompt>"  # Short form

# Structured output - agent returns only matching JSON
paseo run --output-schema '{"type":"object","properties":{"summary":{"type":"string"}},"required":["summary"]}' "<prompt>"
paseo run --output-schema schema.json "<prompt>"  # Or from a file
# NOTE: --output-schema blocks until completion (cannot be used with --detach)
# NOTE: --wait-timeout applies to --output-schema runs too

# Worktrees - isolated git worktree for parallel feature development
paseo run --worktree feature-x "<prompt>"

# Check agent logs/output
paseo logs <agent-id>
paseo logs <agent-id> -f               # Follow (stream)
paseo logs <agent-id> --tail 10        # Last 10 entries
paseo logs <agent-id> --filter tools   # Only tool calls

# Wait for agent to complete or need permission
paseo wait <agent-id>
paseo wait <agent-id> --timeout 60     # 60 second timeout

# Send follow-up prompt to running agent
paseo send <agent-id> "<prompt>"
paseo send <agent-id> --image screenshot.png "<prompt>"  # With image
paseo send <agent-id> --no-wait "<prompt>"               # Queue without waiting

# Inspect agent details
paseo inspect <agent-id>

# Interrupt an agent's current run
paseo stop <agent-id>

# Hard-delete an agent (interrupts first if needed)
paseo delete <agent-id>

# Attach to agent output stream (Ctrl+C to detach without stopping)
paseo attach <agent-id>

# Permissions management
paseo permit ls                # List pending permission requests
paseo permit allow <agent-id>  # Allow all pending for agent
paseo permit deny <agent-id> --all  # Deny all pending

# Agent mode switching
paseo agent mode <agent-id> --list   # Show available modes
paseo agent mode <agent-id> bypass   # Set bypass mode

# Output formats
paseo ls --json          # JSON output
paseo ls -q              # IDs only (quiet mode, useful for scripting)

Available Models

Claude (default provider) - use aliases, CLI resolves to latest version:

  • --model haiku - Fast/cheap, ONLY for tests (not for real work)
  • --model sonnet - Default, good for most tasks
  • --model opus - For harder reasoning, complex debugging

Codex (--provider codex):

  • --model gpt-5.4 - Latest frontier agentic coding model (default, preferred for all engineering tasks)
  • --model gpt-5.1-codex-mini - Cheaper, faster, but less capable

Permissions

Always launch agents fully permissioned. Use --mode bypass for Claude and --mode full-access for Codex. Control behavior through strict prompting, not permission modes.

Agent Use Cases

You can run agents to:

  • Implement a task - Spawn an agent to write code and implement features
  • Have a design discussion - Use Codex for architecture discussions
  • Test some feature - Run tests and verify functionality
  • Do investigation - Research and explore the codebase
  • Review changes - Use Codex for thorough code reviews

Clarifying Ambiguous Requests

CRITICAL: When user requests are ambiguous or unclear:

  1. Research first - Spawn an investigation agent to understand the current state
  2. Ask clarifying questions - After research, ask the user specific questions about what they want
  3. Present options - Offer multiple approaches with trade-offs
  4. Get explicit confirmation - Never assume what the user wants

Investigation vs Implementation

CRITICAL: When asked to investigate:

  • Investigation agents MUST NOT fix issues - They should only identify, document, and report problems
  • Always ask for confirmation - After investigation, present findings and ask: "Should I proceed with implementing fixes?"
  • Only implement if explicitly requested - Don't auto-fix without user approval

Rigorous Agent Interrogation

CRITICAL: Agents start with ZERO context about your task. You must always provide complete context in your initial prompt.

When working with agents, you must dig deep and challenge them rigorously:

For Implementation Agents

  • Don't accept surface-level completion: Check their logs with paseo logs <id>
  • Trace the implementation: Ask them to walk through the code flow step by step
  • Uncover gaps: Send follow-up prompts with paseo send <id> "<question>"
    • "Show me exactly where you handle error case X"
    • "What happens if the user does Y before Z?"
    • "Walk me through the data flow from input to output"

For Investigation/Debugging Agents

  • Don't stop at the first answer: Keep digging deeper
  • Explore different angles: "What are 3 other possible causes?"
  • Request proof: "Show me the specific code that proves this hypothesis"
  • Challenge assumptions: "How do you know that's the root cause?"

For Review Agents (prefer Codex)

  • Security review: "What are the security implications? Any OWASP vulnerabilities?"
  • Edge cases: "What edge cases are not handled?"
  • Performance: "Where are the performance bottlenecks?"
  • Maintainability: "How maintainable is this code?"

Waiting for Agents

CRITICAL: Both paseo run and paseo wait block until the agent completes. Trust them.

  • paseo run waits forever by default (no timeout). Use --wait-timeout to set a limit.
  • paseo wait also waits forever by default. Use --timeout to set a limit.
  • Agent tasks can legitimately take 10, 20, or even 30+ minutes. This is normal.
  • When a wait times out, just re-run paseo wait <id> — don't panic, don't start checking logs, don't inspect status. The agent is still working.
  • Do NOT poll with paseo ls, paseo inspect, or paseo logs in a loop to "check on" the agent. This wastes your context window and accomplishes nothing.
  • Only check logs/inspect if you have a specific reason to believe something is wrong (e.g., you sent a prompt and got an unexpected error back).
  • Never launch a duplicate agent because a wait timed out. The original is still running.
# Correct: just keep waiting
paseo wait <id>              # timed out? just run it again:
paseo wait <id>              # still going? keep waiting:
paseo wait <id> --timeout 300  # or use a longer timeout

# For long-running tasks, set a generous timeout on run itself:
paseo run --wait-timeout 1h --output-schema '...' "<prompt>"

# Wrong: anxious polling loop
paseo wait <id>    # timed out
paseo ls           # is it still running??
paseo inspect <id> # what's it doing??
paseo logs <id>    # let me check the logs!!
# ^ Don't do this. Trust the wait.

Agent Management Principles

  • Keep agents focused - Each agent should have a clear, specific responsibility
  • You can talk to them - Use paseo send <id> "<prompt>" to guide them
  • Monitor progress - Use paseo logs <id> -f to stream output
  • Always provide context - Remember: agents start with zero knowledge of your task
  • Verify work rigorously - Don't trust, verify. Ask agents to prove their work
  • Commit frequently - Ensure each agent commits their changes before moving on
  • Plan for quality gates - Use Codex review agents as checkpoints
  • Run in parallel when possible - Use -d flag to run multiple agents concurrently

Common Patterns

Committee

When stuck or planning something hard, use the /committee skill. It launches two high-reasoning agents (Opus 4.6 + GPT 5.4) in parallel to do root cause analysis and produce a plan, then stays alive to review the implementation afterward.

Composing Agents in Bash Scripts

paseo run blocks by default and --output-schema returns structured JSON, making it easy to compose agents in bash loops and pipelines.

Implement-and-verify loop:

while true; do
  paseo run --provider codex "make the tests pass" >/dev/null

  verdict=$(paseo run --provider claude --output-schema '{"type":"object","properties":{"criteria_met":{"type":"boolean"}},"required":["criteria_met"],"additionalProperties":false}' "ensure tests all pass")
  if echo "$verdict" | jq -e '.criteria_met == true' >/dev/null; then
    echo "criteria met"
    break
  fi
done

Detach + wait pattern for parallel work:

# Kick off parallel agents
api_id=$(paseo run -d --name "API impl" "implement the API" -q)
ui_id=$(paseo run -d --name "UI impl" "implement the UI" -q)

# Wait for both to finish
paseo wait "$api_id"
paseo wait "$ui_id"

# Review the combined result
paseo run --provider codex "review the API and UI implementations. DO NOT edit."

Source Transparency

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