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.
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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
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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.
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