ai project execution planner

    1

    Converts vague technical goals into scoped, sequenced execution plans with verifiable tasks and dependency mapping.

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    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+21 more

    ai project execution planner

    Example session with this skill installed

    I need a plan to add a 'dark mode' toggle to our Next.js dashboard. It should persist in localStorage and respect system preferences. Check the components folder to see how we handle themes.

    • Read your context and instructions
    • Compiled the ai project execution

    I have analyzed the dashboard components and drafted a sequenced execution plan. This plan focuses on a persistent theme provider that respects both user overrides and system settings.

    Project: Dashboard Dark Mode Persistence

    Outcome

    A user can toggle between light and dark themes via a UI switch, and their preference persists across page reloads and browser sessions.

    Scope

    In

    • Theme provider implementation using Next-Themes.
    • UI Toggle component in the Navigation sidebar.
    • LocalStorage persistence logic.
    • System preference detection (prefers-color-scheme).

    Out

    • Redesigning existing component colors (uses current CSS variables).
    • Different themes for sub-domains.

    Dependencies

    DependencyTypeStatus
    next-themes packagebuild-firstNot installed
    layout.tsxexistsNeeds wrap
    components/Nav.tsxexistsNeeds toggle

    Reusable Context

    • CSS Variables: --background, --foreground, --primary.
    • Config: Next.js 14 App Router conventions.
    • Storage Key: theme-preference.

    Execution Plan

    Milestone 1: Theme Infrastructure

    Outcome: The application can programmatically switch CSS variable sets.

    Task 1.1: Install and Wrap Provider
    • Touches: package.json, app/layout.tsx

    Agent instruction: Install next-themes and wrap the root layout with the ThemeProvider, setting the attribute to 'class'.

    • Verification: grep package.json for the dependency and check layout.tsx for the provider wrapper.
    • Handoff: Provider is active; useTheme hook is now available for components.

    Milestone 2: UI Implementation

    Outcome: User can interactively change the theme state.

    Task 2.1: Create ThemeToggle Component
    • Touches: components/ThemeToggle.tsx

    Agent instruction: Build a client component switch that calls setTheme. Ensure it handles hydration mismatch by only rendering after mount.

    • Verification: Run the component in isolation or check for useEffect mount guard in code.
    • Handoff: Toggle component is ready for placement.

    Sequenced Task List (priority order)

    1. [Milestone 1] Task 1.1 — Install and Wrap Provider.
    2. [Milestone 2] Task 2.1 — Create ThemeToggle Component.
    3. [Milestone 2] Task 2.2 — Integrate Toggle into components/Nav.tsx.

    Closure Checklist

    • Theme persists after manual browser refresh.
    • Dashboard defaults to dark if system prefers-color-scheme is dark.
    • No hydration mismatch warnings in console.

    Next steps

    1. Install next-themes dependency.
    2. Implement the ThemeProvider in the root layout.
    3. Verify the CSS variable mapping in your global stylesheet.
    package.json

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    About this skill

    The problem

    Vague feature requests and Slack threads often lead to scope creep, blocked workstreams, and failed agent handoffs. Without a concrete sequence of verifiable tasks, developers waste time re-deriving context or building the wrong thing.

    What it does

    • Extracts observable success criteria from ambiguous goals to define a "true done" state.
    • Maps codebase dependencies by reading existing files to ground the plan in reality.
    • Decomposes projects into sequenced milestones with atomic, verb-first tasks.
    • Generates specific verification gates and handoff instructions for every task to ensure seamless execution.
    • Captures reusable context like API shapes and config paths upfront for future sessions.

    Why this beats prompting it yourself

    Most LLMs jump straight into writing code, leading to circular dependencies and missed edge cases. This skill enforces a rigorous planning phase that separates architectural intent from implementation, producing a document that serves as a verifiable source of truth for both humans and other agents.

    Use cases

    • Breaking down a complex feature request into a multi-day execution roadmap.
    • Creating clear handoff documentation for sub-agents to execute specific modules.
    • Auditing a stalled project to identify hidden blocks and missing acceptance criteria.
    • Scoping the MVP of a new service to prevent unnecessary engineering overhead.

    Known limitations

    Does not execute the plan, write production code, or manage infrastructure. Requires read access to the project directory to surface accurate dependencies.

    Does not execute code or run builds. Requires read-only access to relevant files to avoid assumptions. Best for projects with at least one sentence of initial goal description.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

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    What's inside

    Frequently Asked Questions

    This skill analyzes your technical goals and codebase to generate a structured roadmap of atomic tasks, success criteria, and dependency maps, preventing scope creep and 'stalled' projects.

    It is designed to work within any AI agent environment that has file-system read access, such as AutoGPT, OpenDevin, or custom LangChain agents.

    Simply add the skill to your agent's library and ensure it has read permissions for your project directory so it can map existing dependencies accurately.

    No, this skill is a specialized architect; it produces the 'source of truth' documentation and sequenced tasks that you or a separate coding agent then execute.

    You receive the core logic for the planning workflow, documentation on integrating it into your agent's toolset, and access to any version updates released by the creator.

    Yes, the planner is designed to output standardized verification gates for every task, making it ideal for creating clear instructions for sub-agents to follow.

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