config.example.toml

[server]
listen = "0.0.0.0:9090"

[security]
webhook_secrets = ["your-secret-here"]
allow_unsigned = true  # dev only

# Feature flags: all new Phase-B paths default OFF.
[features]
tunnel_enabled = false
cli_enabled = false
callback_enabled = false

# Runtime guardrails
[runtime]
cli_max_concurrency = 1
http_timeout_secs = 15
tunnel_reconnect_backoff_max_secs = 60

# Optional: tunnel config (Phase B minimal viable)
[tunnel]
enabled = false
# supports ws:// and wss://, production should use wss://
url = "wss://openpr.example.com/api/v1/agent-tunnel"
agent_id = "vano-qa"
# sent as Authorization: Bearer <token>
auth_token = "opr_xxx"
# auto reconnect interval after disconnect/failure
reconnect_secs = 3
# heartbeat send interval
heartbeat_secs = 20
# optional: sign outgoing envelopes and verify incoming envelopes
hmac_secret = "shared-hmac-secret"
# if true, inbound tunnel messages without sig are rejected
require_inbound_sig = false

[[agents]]
id = "david"
name = "David"
agent_type = "openclaw"
message_template = "🔔 [{project}] {event}: {key} {title}\n👤 {actor} | Trigger: {reason}"

[agents.openclaw]
command = "openclaw message send"
channel = "signal"
target = "uuid:your-user-uuid"

[[agents]]
id = "vano-cli"
name = "Vano CLI"
agent_type = "cli"
message_template = "[{project}] {event}: {key} {title}"

[agents.cli]
executor = "codex" # codex | claude-code | opencode
workdir = "/opt/worker/code/openpr"
timeout_secs = 900
max_output_chars = 12000
prompt_template = "Fix issue {issue_id}: {title}\nContext: {reason}"
callback = "mcp" # mcp | api
callback_url = "http://127.0.0.1:8090/mcp/rpc"
callback_token = "opr_xxx"
update_state_on_start = "in_progress"
update_state_on_success = "done"
update_state_on_fail = "todo"

# --- MCP closed-loop example (AI reads full issue context via MCP) ---

[[agents]]
id = "ai-fixer"
name = "AI Issue Fixer"
agent_type = "cli"

[agents.cli]
executor = "claude-code"
workdir = "/opt/worker/code/openpr"
timeout_secs = 900
max_output_chars = 12000
prompt_template = "Fix issue {issue_id}: {title}\nContext: {reason}"

# MCP closed-loop: AI updates issue state directly via MCP tools,
# so we skip the callback state update to avoid duplication.
skip_callback_state = true
callback = "mcp"
callback_url = "http://127.0.0.1:8090/mcp/rpc"
callback_token = "opr_xxx"

# Optional: path to MCP config for claude-code (--mcp-config flag).
# If omitted, claude-code uses its global ~/.claude.json MCP config.
# mcp_config_path = "/path/to/mcp-config.json"

# Custom MCP instructions appended to the prompt. If omitted, a sensible
# default is used that instructs the AI to read/write via OpenPR MCP tools.
# mcp_instructions = "Use work_items.get to read issue {issue_id}, then fix it."

# Extra environment variables injected into the executor subprocess.
# Useful for per-agent API URLs, bot tokens, or workspace IDs.
[agents.cli.env_vars]
OPENPR_API_URL = "http://localhost:3000"
OPENPR_BOT_TOKEN = "opr_xxx"
OPENPR_WORKSPACE_ID = "e5166fd1-..."