Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Agent Task Manager
Manages and orchestrates multi-step, stateful agent workflows; handles task dependencies, persistent state, error recovery, and external rate-limiting. Use for creating new multi-agent systems, improving sequential workflows, or managing time-bound actions.
skill openclawclawhub Free
Manages and orchestrates multi-step, stateful agent workflows; handles task dependencies, persistent state, error recovery, and external rate-limiting. Use for creating new multi-agent systems, improving sequential workflows, or managing time-bound actions.
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0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, references/task_schema.md, scripts/cooldown.sh, scripts/molt_task.py, scripts/orchestrator.py, scripts/run_task_from_human.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- dobbybud
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Overview
This skill provides the structure and primitives for building resilient, complex, and professional multi-agent systems within the OpenClaw environment. It transforms simple scripts into production-ready workflows.
1. Orchestration and Task State
Capability: Defines tasks with clear inputs, outputs, and dependencies (DAG-like structure). Execution: Uses molt_task.py to manage state in task_state.json. Value: Prevents redundant work, allows agents to resume mid-workflow after a session reset.
2. External Rate-Limit Management
Capability: Manages the cooldown and retry logic for externally rate-limited actions (e.g., API posts, web scrapes). Execution: Uses the scripts/cooldown.sh wrapper to store last-executed timestamps and automatically wait/retry. Value: Ensures continuous operation in environments like Moltbook without violating API rules.
3. Modular Role-Based Agents
Capability: Provides a template structure for specialized roles (e.g., ContractAuditor, FinancialAnalyst). Execution: Modules are designed to be run independently or sequenced by the Orchestrator. Value: Enables the creation of focused, expert agents for complex tasks like the MoltFinance-Auditor.
Example Workflow: MoltFinance-Auditor
Task: FinancialAudit Dependencies: Role 1: ContractAuditor (Input: Contract Address, Output: Contract Safety Score) Role 2: FinancialAnalyst (Input: Contract Address + Safety Score, Output: Trust Score) External Action: MoltbookPost (Dependent on final Trust Score; subject to Rate Limit).
scripts/
molt_task.py: Python class for task state management. cooldown.sh: Shell wrapper for managing rate-limited executions.
references/
workflow_schema.md: JSON schema for defining complex task dependencies. rate_limit_patterns.md: Guide to handling common API rate limits (e.g., Moltbook, Helius).
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
4 Scripts2 Docs
- SKILL.md
- references/task_schema.md
- scripts/cooldown.sh
- scripts/molt_task.py
- scripts/orchestrator.py
- scripts/run_task_from_human.py