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dingdawg-loop
Advanced tools
DingDawg Loop Protocol (DDLP) — safe scheduled AI agents with governance gates. Every loop execution is verified, receipted, and fail-closed. MCP-native, works with CrewAI, LangGraph, Claude Code, Cursor.
DingDawg Loop Protocol (DDLP) — a framework for safe, scheduled, proactive AI agents with built-in governance gates. Agents declare what they WILL do, pass a governance check, and only then execute. If governance denies or errors, the loop skips that cycle. Fail-closed by default — no silent autonomous action.
AI agents running on a schedule without governance is a liability. An agent that sends emails every hour, syncs data nightly, or processes payments weekly needs a gate between "I want to act" and "I acted." DDLP puts that gate in place: every scheduled execution is governed, audited, and reversible. Proactive agents become safe by default.
# Add to Claude Code
claude mcp add dingdawg-loop npx dingdawg-loop
# Or run directly
npx dingdawg-loop
{
"tool": "register_loop",
"arguments": {
"name": "daily-report-sender",
"schedule": "0 9 * * *",
"action_type": "generate_report",
"risk_tier": "low",
"description": "Generate and save a daily analytics summary report to the reports directory every morning at 9am."
}
}
Returns a loop_id you use for all subsequent operations.
{
"tool": "execute_loop",
"arguments": {
"loop_id": "loop_abc123",
"execution_notes": "Manual trigger for Monday report"
}
}
The governance gate evaluates the loop's action type, description, and risk tier. Three possible outcomes:
{
"tool": "loop_audit",
"arguments": {
"loop_id": "loop_abc123",
"limit": 10
}
}
Returns every execution with its governance decision, risk score, and outcome.
register_loopRegister a new scheduled agent loop.
| Parameter | Type | Required | Description |
|---|---|---|---|
name | string | yes | Unique human-readable name for this loop |
schedule | string | yes | Cron expression (0 9 * * *) or shorthand (@hourly, @daily) |
action_type | string | yes | What the loop does (send_email, generate_report, sync_data) |
risk_tier | enum | yes | low, medium, high, or critical |
description | string | yes | Detailed description (min 10 chars) — governance evaluates this |
metadata | object | no | Key-value pairs (owner, team, target_system) |
execute_loopManually trigger a loop. Governance gate runs BEFORE execution.
| Parameter | Type | Required | Description |
|---|---|---|---|
loop_id | string | yes | The loop_id from register_loop |
execution_notes | string | no | Why this manual execution was triggered |
list_loopsList all registered loops with status and last execution.
| Parameter | Type | Required | Description |
|---|---|---|---|
status_filter | enum | no | all, active, or paused (default: all) |
pause_loopPause a loop so it cannot be executed.
| Parameter | Type | Required | Description |
|---|---|---|---|
loop_id | string | yes | The loop_id to pause |
reason | string | no | Why this loop is being paused |
resume_loopResume a paused loop.
| Parameter | Type | Required | Description |
|---|---|---|---|
loop_id | string | yes | The loop_id to resume |
loop_auditGet execution history and governance decisions for a loop.
| Parameter | Type | Required | Description |
|---|---|---|---|
loop_id | string | yes | The loop_id to audit |
limit | number | no | Max records to return (default: 20) |
~/.dingdawg/loops/executions/ as JSON.execute_loop calls in v1. No background daemon.DDLP requires dingdawg-governance as a peer dependency. In v1, the governance logic runs locally inside the loop server. In v2+, it will call the governance server directly via MCP-to-MCP transport.
npm install dingdawg-governance dingdawg-loop
Loop definitions and execution records are stored locally:
~/.dingdawg/loops/
loop_abc123.json # loop definition
executions/
exec_xyz789.json # execution record with governance receipt
execute_loop. Schedule stored but not auto-executed.MIT
FAQs
Governance receipts for AI agents — DingDawg Loop Protocol (DDLP) for safe scheduled agents with governance gates, compliant with EU AI Act Art. 12, Colorado AI Act (SB 24-205), and NIST AI RMF. Every loop execution is verified, receipted, and fail-closed
The npm package dingdawg-loop receives a total of 16 weekly downloads. As such, dingdawg-loop popularity was classified as not popular.
We found that dingdawg-loop demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.

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