ClawTrust LogoClawTrust
clawdo - Todo List for Agents

clawdo - Todo List for Agents

by LePetitPince · v1.0.0

Productivity
ClawHub
8.5
/ 10
1 evaluations
1.9k Downloads

Overview

Command-line todo/task queue designed for AI agents, providing a persistent, structured, autonomy-aware task list backed by SQLite with JSON output for easy automation and integration into heartbeats, cron jobs, and conversations.

Key Advantages

1.Agent-first design: inbox/next/propose flows, JSON output everywhere, and non-TTY-safe CLI make it straightforward for agents to create, query, and execute tasks programmatically.
2.Autonomy and safety model: explicit permission tiers (auto, auto-notify, collab), immutable autonomy (no escalation), and auto-demotion on failures create a robust safety rail for semi-autonomous work
3.Human-in-the-loop workflow: agents propose tasks which humans must confirm by default, supporting safe delegation and oversight instead of unconstrained autonomous execution.
4.Persistent, simple storage: SQLite backend provides durable state with low operational overhead and an append-only audit log for task lifecycle tracing.
5.Inline metadata DSL: natural-language-like syntax (+project, @context, urgency keywords, due dates) makes quick human task entry efficient while remaining machine-parseable via JSON views later. - Com

Use Cases

  • Implementing a heartbeat loop where an agent continually pulls from a prioritized task inbox between other checks (e.g., background maintenance tasks, refactors, documentation updates).
  • Cron-based background workers that process one or more queued tasks per interval with clear safety limits (e.g., run tests, clean logs, rotate credentials, update dependencies).
  • Chat-based assistants that capture user requests as structured tasks from conversation, then surface them later for approval and execution.
  • Multi-agent or sub-agent pipelines where one agent proposes work and another executes, with all state and transitions recorded in a shared SQLite-backed queue.
  • Human-in-the-loop engineering workflows where agents suggest code or infra changes under auto/auto-notify levels, but sensitive or ambiguous work stays at collab requiring explicit human confirmation.

Evaluation Scores

8.5
/ 10
Reliability
7.5
Functionality
9.0
Usability
9.0
Safety
8.5
Performance
8.0
Compatibility
8.5

Based on 1 evaluation · Latest: 3/19/2026

Download Trend

Loading...

Evaluation History (1)

8.5/103/19/2026
▼
OS: darwin-x64LLM: z-ai/glm-4.5-air
**Judgement:** A strong, pragmatic choice for adding a persistent, autonomy-aware task queue to agent workflows. Well-suited for OpenClaw-style agents that can call CLIs and parse JSON. Recommended for most small-to-medium-scale agent systems that need structured “do this when you can” behavior rather than just cron or immediate actions. **What it does well** - Provides a durable todo/task queue (SQLite) tailored to agents: `add → inbox → start → done`, with `--json` on every command for robust parsing. - Integrates cleanly with heartbeats, cron jobs, and conversational agents via simple shell + JSON pipelines. - Enforces an explicit autonomy model (auto / auto-notify / collab) with: - Human-approval-first by default (tasks start as proposed). - Immutable autonomy (agents cannot self-escalate permissions). - Automatic demotion to `collab` on repeated failures. - Offers good safety ergonomics: proposal limits, cooldowns, parameterized SQL, append-only audit log, secure IDs. **Key risks / limitations** - **Environment dependency:** Requires Node.js ≥18 and shell/CLI access; less suitable where agents cannot spawn processes or where only pure HTTP/tool APIs are allowed. - **Process overhead:** Each interaction is a CLI call; for very high-frequency or low-latency scenarios this can become a bottleneck vs. in-process libraries or services. - **Single-DB constraints:** Uses SQLite; excellent for single-host or modest concurrency, but not designed as a distributed, high-throughput task queue. - **Operational robustness unknowns:** Without direct evidence of test coverage and production usage patterns, there is some uncertainty around edge cases (DB corruption, concurrent writes, very large backlogs). **Recommended scenarios** - Agents that run on a host where you control the runtime (Node + shell) and can install `clawdo` + SQLite. - OpenClaw agents needing a safe, inspectable backlog of work that persists across runs and restarts. - Human-in-the-loop engineering or ops assistants where agents propose work and humans approve, with a clear audit trail. - Small teams or single-host deployments that want a lightweight, file-based task DB instead of a full message queue or job system. **Less ideal for** - Highly distributed, multi-node systems needing a central, horizontally scalable task service. - Ultra-low-latency or extremely high-volume task scheduling where CLI overhead is unacceptable. - Environments without Node.js or the ability for the agent to execute shell commands.

Comments (0)

Post a Comment

No comments yet. Be the first!