agent-planner_skill

This skill helps orchestrate complex tasks by decomposing objectives, mapping dependencies, allocating resources, and estimating timelines for actionable plans.
  • TypeScript

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Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill ruvnet/ruflo --skill agent-planner

  • SKILL.md4.6 KB

Overview

This skill is a strategic planning and task orchestration agent invoked with $agent-planner. It breaks down complex goals into actionable plans, assigns agents and resources, estimates timelines, and flags risks so multi-agent workflows execute reliably. Use it to convert high-level objectives into measurable phases with clear dependencies and success criteria.

How this skill works

The planner analyzes the full scope of a request, decomposes it into atomic tasks, and maps dependencies to reveal the critical path. It allocates agents and resources, produces timeline estimates, and generates risk assessments and mitigation steps. Outputs follow a structured plan format (objective, phases, tasks, critical_path, risks, success_criteria) and can be stored or broadcast via MCP memory hooks for swarm coordination.

When to use it

  • Launching multi-agent projects that require coordinated task handoffs and parallel execution
  • Designing implementation roadmaps from vague or high-level requirements
  • Allocating limited compute or human resources across interdependent tasks
  • Estimating timelines and identifying the critical path before execution
  • Creating contingency plans and checkpoint validations for high-risk initiatives

Best practices

  • Start with a clear objective and measurable success criteria to guide decomposition
  • Break work into atomic, testable tasks with explicit inputs, outputs, and owners
  • Map dependencies early and highlight critical-path tasks to prioritize effort
  • Allocate resources for parallelism when safe, but plan validation checkpoints
  • Store plans and status in shared memory so other agents can read and act

Example use cases

  • Plan and orchestrate an authentication subsystem: research, design, implement, test, deploy
  • Turn a product feature request into phased implementation tasks with agent assignments
  • Coordinate a data-pipeline build across data engineers, modelers, and QA agents
  • Estimate rollout timelines and contingency plans for a multi-region deployment
  • Create a mitigation plan for a high-risk integration involving third-party APIs

FAQ

A structured plan including objective, phases with tasks (id, description, agent, dependencies, estimated_time, priority), critical_path, risks with mitigations, and success_criteria.

How does it coordinate with other agents?

Plans and status entries are written to shared memory via MCP hooks so other agents can read assignments, update progress, and trigger follow-up actions.

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agent-planner skill by ruvnet/ruflo | VeilStrat