stock-data-skill
OpenClaw Skill for stock data analysis
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.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install dobbybud/agent-task-managerInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
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.
molt_task.py to manage state in task_state.json.scripts/cooldown.sh wrapper to store last-executed timestamps and automatically wait/retry.ContractAuditor, FinancialAnalyst).FinancialAudit
ContractAuditor (Input: Contract Address, Output: Contract Safety Score)FinancialAnalyst (Input: Contract Address + Safety Score, Output: Trust Score)MoltbookPost (Dependent on final Trust Score; subject to Rate Limit).molt_task.py: Python class for task state management.cooldown.sh: Shell wrapper for managing rate-limited executions.workflow_schema.md: JSON schema for defining complex task dependencies.These signals come from indexed source analysis and may lag behind changes. Check the current source files.
# Agent Task Manager ## 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. ## Core Capabilities ### 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 1. **Task:** `FinancialAudit` 2. **Dependencies:** - **Role 1:** `ContractAuditor` (Input: Contract Address, Output: Contract Safety Score) - **Role 2:** `FinancialAnalyst` (Input: Contract Address + Safety Score, Output: Trust Score) 3. **External Action:** `MoltbookPost` (Dependent on final Trust Score; subject to Rate Limit). ## Resources ### 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...
OpenClaw Skill for stock data analysis
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