skills.rest
vecear
vecearCOMMUNITY
Explore all skills by this author →
GitHub

agent-orchestration-planner

Plan multi-tool agent workflows with retry logic, memory, and budget tracking.

Updated Jan 21, 2026
Search Tags:#planning#agent#orchestration#budget#state-management#tools#retry
One-click install
npx skills add https://github.com/vecear/Nipponverb --skill agent-orchestration-planner-vecear
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-orchestration-planner
Source: https://github.com/vecear/Nipponverb/tree/main/.claude/skills/agent-orchestration-planner
Command: npx skills add https://github.com/vecear/Nipponverb --skill agent-orchestration-planner-vecear

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Designs multi-step agent workflows with tool usage, retry logic, state management, and budget controls. Provides orchestration diagrams, tool execution order, fallback strategies, and cost limits. Use for "AI agents", "agentic workflows", "multi-step AI", or "autonomous systems".

Core Features & Use Cases

  • Planning and tool selection to compose complex agent workflows
  • Retry logic, fallback strategies, and error handling for reliable execution
  • State management and memory tracking to preserve context across steps
  • Budget controls and cost tracking to prevent runaway executions
  • Multi-agent coordination patterns and orchestration diagrams for clarity

Quick Start

Design a multi-step agent workflow that coordinates a web search tool, a database query, and a content generator while enforcing retries, memory logging, and a budget cap.

Frequently Asked Questions about agent-orchestration-planner

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I orchestrate multi-step AI agent workflows with tool selection and fallback strategies?▼

Multi-step AI agent workflows are orchestrated by specifying tool selection order, fallback strategies, and state persistence. This ensures reliable tool execution across planning, validation, and cost management in a deterministic, safe way.

What is the best way to add retry logic and error handling to autonomous AI agents?▼

Retry logic and error handling for autonomous AI agents are added by defining fallback strategies and tool execution orders within the workflow. This guarantees reliable outcomes when tool orchestration encounters execution failures.

How does state management and memory tracking work across multi-step agentic workflows?▼

State management and memory tracking in agentic workflows preserve context across execution steps. By persisting state, the workflow maintains continuity between tool selections, validation phases, and multi-agent coordination patterns.

Can I enforce budget controls and cost tracking to prevent runaway AI agent executions?▼

Budget controls and cost tracking prevent runaway AI agent executions by enforcing cost limits within the orchestration workflow. This caps multi-step tool usage and ensures deterministic, safe execution within allocated resources.

Does this support multi-agent coordination patterns for complex tool orchestration?▼

Multi-agent coordination patterns for complex tool orchestration are supported through detailed orchestration diagrams. These diagrams specify tool selection order, state persistence, and fallback strategies to ensure reliable coordinated outcomes.

When should I not use a deterministic orchestration planner for AI agents?▼

A deterministic orchestration planner should not be used for AI agents when workflows require spontaneous tool selection outside defined fallback strategies, or when execution lacks clear state persistence and budget control requirements.

Related Skills

Explore More Software Engineering Skills→
1molchuan1molchuan
1

oh-my-ccg-init

Verify MCP, Codex, and Gemini endpoints and initialize RPI state.

Community
Intermediate
patricio0312revpatricio0312rev
5

agent-orchestration-planner

Design multi-step agent workflows with tools, retry logic, and state management.

Community
Advanced
arbazkhan971arbazkhan971
26

agent

Design and validate autonomous AI agents with tool orchestration and guardrails.

Community
Advanced
tfunk1030tfunk1030
1

multi-tool-pipeline

Chain MCP tools into reusable pipelines with sequential execution and error handling.

Community
Intermediate