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roadmap-skill
by shiquda

Roadmap Skill

AI-readable docs: llms.txt · llms-full.txt · Architecture · Tool Interface Standard


What Makes It Different

Shared context — Chat with your Agent to plan tasks, or edit directly in the Kanban — both stay in sync. Your Agent always sees the latest state.

Agent-native — Built as an MCP server. Your AI can create, update, and query tasks directly in conversation.

Visual workspace — Open localhost:7860 when you feel like it, or ask your Agent to open it with open_web_interface. Kanban for status, Graph View for sequencing. Or just stay in chat. All three work.

Local-first — Your data lives on your machine. No accounts, no cloud sync, no vendor lock-in.


Related MCP server: crunchy-work

New in v0.3.0: Graph View

Graph View is one of the headline features in v0.3.0.

Kanban is great for tracking status. Graph View is for understanding execution order.

It helps you and your Agent answer questions like:

  • What has to happen first?

  • Which tasks are ready right now?

  • What is blocked by unfinished work?

  • Which dependency should be added, reversed, or removed?

Instead of treating roadmap tasks as a flat list, Graph View turns them into a visual dependency map with node connections, ready/done states, detailed task cards, and export support. It is designed for planning sessions where sequencing matters just as much as status.

If you are using Roadmap Skill as an MCP workspace, this is the view that makes agent-assisted planning feel concrete: your Agent can build and update dependency graphs in chat, and you can immediately inspect the structure visually in the web UI.


Quick Start (Zero Config)

# Integrate with your AI assistant (MCP config below)
claude mcp add roadmap "npx -y roadmap-skill"
{
  "mcpServers": {
    "roadmap": {
      "command": "npx",
      "args": ["-y", "roadmap-skill"]
    }
  }
}
/mcp add

Or edit ~/.copilot/mcp-config.json:

{
  "mcpServers": {
    "roadmap": {
      "type": "local",
      "command": "npx",
      "args": ["-y", "roadmap-skill"]
    }
  }
}
{
  "mcpServers": {
    "roadmap": {
      "command": "npx",
      "args": ["-y", "roadmap-skill"]
    }
  }
}

Install Cline plugin, then add to cline_mcp_settings.json:

{
  "mcpServers": {
    "roadmap": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "roadmap-skill"]
    }
  }
}
{
  "mcpServers": {
    "roadmap": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "roadmap-skill"]
    }
  }
}

Edit ~/.config/opencode/opencode.json:

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "roadmap": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "roadmap-skill"
      ],
      "enabled": true
    }
  }
}

Go to Settings -> MCP -> Add new MCP Server:

{
  "mcpServers": {
    "roadmap": {
      "command": "npx",
      "args": ["-y", "roadmap-skill"]
    }
  }
}
{
  "mcp": {
    "servers": {
      "roadmap": {
        "command": "npx",
        "args": ["-y", "roadmap-skill"]
      }
    }
  }
}

Follow Windsurf MCP documentation and use:

{
  "mcpServers": {
    "roadmap": {
      "command": "npx",
      "args": ["-y", "roadmap-skill"]
    }
  }
}
{
  "context_servers": {
    "roadmap": {
      "command": {
        "path": "npx",
        "args": ["-y", "roadmap-skill"]
      }
    }
  }
}

One-liner (recommended):

codex mcp add roadmap -- npx -y roadmap-skill

Manual config — edit ~/.codex/config.toml:

[mcp_servers.roadmap]
command = "npx"
args = ["-y", "roadmap-skill"]

Windows: No cmd /c wrapper needed — Codex handles the subprocess directly.

Server name: Must match ^[a-zA-Z0-9_-]+$. Names with spaces or parentheses are rejected.

Note: Both Codex CLI and the Codex VSCode extension share the same ~/.codex/config.toml. A syntax error breaks both.

After setup, simply tell your AI:

"Create a website redesign project with tasks for homepage, about page, and contact form"

The AI will immediately create the project and tasks, saving them to local storage. You can open http://localhost:7860 anytime to view the visual Kanban board.


Agent Skills

This repository includes installable skills under skills/, distributed through the git repository rather than the published npm package.

Available skills:

  • skills/roadmap/ - lightweight background and routing for roadmap-skill

  • skills/roadmap-task-flow/ - capture, enrich, tag, and prioritize roadmap tasks

  • skills/roadmap-planning-views/ - build focused planning graphs from task subsets

  • skills/roadmap-web-visualization/ - open and use the local roadmap web workspace

Recommended installation pattern for skill-aware tools:

# install from the git repository when the installer supports repo sources
npx skills add shiquda/roadmap-skill

These skills are still in beta. If you run into issues or have suggestions, feedback is very welcome.


Who Is This For?

Solo developers, AI power users, and vibe coders who want their Agent to be a real collaborator — not just a code generator.


Typical Use Cases

1. Capture Ideas Without Breaking Flow

Mid-session, something pops into your head:

"Note this down: switch the auth module to JWT + refresh token rotation"

Use /quick-capture or just say "help me note this down" — your Agent turns it into a task, saves it locally, and you keep going. No context switch, no forgotten ideas.

2. Let Agent Help You Prioritize

"This month's OKR is finishing the user system refactor — can you list the related tasks and figure out which ones should come first?"

Use /auto-prioritize to let your Agent analyze the current project state and reorder task priorities accordingly.

3. Let Agent Recommend What to Do Next

"What's left on the current project? Any high-priority tasks I haven't touched yet?"

Or use /suggest-tasks — your Agent recommends the next actions based on current progress and priorities.

No tab switching. No copy-pasting. Just ask

Core Features

Feature

Description

Kanban View

Four columns: Todo, In Progress, Review, Done

Graph View

Visual dependency map for sequencing work, spotting blockers, and reviewing execution order

Ready / Blocked Signals

Quickly see which tasks are ready now and which ones still depend on unfinished work

Dependency Editing

Add, reverse, and remove task dependencies directly from the planning graph

Graph Export

Export dependency graphs as images for sharing, review, or release planning

Drag and Drop

Drag tasks to update status, WYSIWYG

Quick Create

Click "+" button on any column to instantly add tasks

Dual View

Compact mode for overview, detailed mode for full info

Smart Search

Quick task search across all projects, keyword filtering


Supported Platforms

  • ✅ Claude Code, Codex, OpenCode — Command-line AI assistants

  • ✅ Cursor, VS Code — AI-powered IDEs

  • ✅ Any MCP Client — Standard MCP protocol support


Data Storage

Roadmap Skill uses pure local JSON file storage. All data is saved in your user directory:

Platform

Storage Path

Windows

%USERPROFILE%\.roadmap-skill

macOS

~/.roadmap-skill/

Linux

~/.roadmap-skill/

You can export or import backup files from the web interface.


License

MIT © shiquda


Available Tools

31 tools
add_dependency_view_edgeA

Create a dependency edge between two tasks already present in a dependency planning view. Returns summary plus changed ids by default; set verbose=true for full data.

Inputs: viewId (required), toTaskId (required), projectId (required), fromTaskId (required), +1 more.

add_task_to_dependency_viewA

Add an existing task into a dependency planning view. Returns summary plus changed ids by default; set verbose=true for full data.

Inputs: taskId (required), viewId (required), projectId (required), x, +4 more.

analyze_dependency_viewA

Analyze a dependency planning view and return topological layers, ready tasks, blocked tasks, roots, leaves, and isolated tasks.

Inputs: viewId (required), projectId (required).

batch_update_dependency_view_nodesA

Update multiple task node layouts or notes inside a dependency planning view. Returns summary plus changed ids by default; set verbose=true for full data.

Inputs: nodes (required), viewId (required), projectId (required), verbose.

batch_update_tasksA

Update multiple tasks at once. tags must be existing tag IDs from the same project. Returns summaries by default; set verbose=true for full task data.

Inputs: taskIds (required), projectId (required), tags, status, +3 more.

close_web_interfaceB

Close web visualization interface

Inputs: no named parameters.

create_dependency_viewA

Create a dependency planning view inside a project. Returns summary by default; set verbose=true for full data.

Inputs: name (required), projectId (required), verbose, dimension, +1 more.

create_projectC

Create a new project roadmap. Returns summary by default; set verbose=true for full data.

Inputs: name (required), startDate (required), targetDate (required), description (required), +2 more.

create_tagB

Create a new tag in a project. If color is omitted, it is generated deterministically from tag name.

Inputs: name (required), projectId (required), color, description.

create_taskA

Create a new task in a project. tags must be existing tag IDs from the same project. Returns summary by default; set verbose=true for full data.

Inputs: title (required), projectId (required), description (required), tags, +4 more.

delete_dependency_viewB

Delete a dependency planning view by project ID and view ID

Inputs: viewId (required), projectId (required).

delete_projectB

Delete a project by ID

Inputs: projectId (required).

delete_tagB

Delete a tag by project ID and tag ID

Inputs: tagId (required), projectId (required).

delete_taskB

Delete a task by project ID and task ID

Inputs: taskId (required), projectId (required).

get_dependency_viewA

Get a dependency planning view by project ID and view ID. Returns Agent-friendly task snapshots by default; set verbose=true for raw node and edge data.

Inputs: viewId (required), projectId (required), verbose.

get_projectA

Get a project by ID with all its data (tasks, tags, milestones). Tasks are returned as summaries by default; set verbose=true for full task data.

Inputs: projectId (required), verbose.

get_taskA

Get a specific task by project ID and task ID

Inputs: taskId (required), projectId (required).

get_tasks_by_tagB

Get all tasks that have a specific tag

Inputs: tagName (required), projectId (required).

list_dependency_viewsA

List dependency planning views in a project. Returns summaries by default; set includeTasks=true for Agent-friendly task snapshots or verbose=true for raw node and edge data.

Inputs: projectId (required), verbose, includeTasks.

list_projectsA

List all projects. Summary mode includes current project tags for Agent reuse. Set verbose=true for full project data.

Inputs: verbose.

list_tagsB

List all tags in a project

Inputs: projectId (required).

list_tasksA

List tasks with optional filters. By default, completed (done) tasks are excluded. Set includeCompleted=true to include them. Returns summaries by default; set verbose=true for full task data.

Inputs: tags, status, verbose, assignee, +5 more.

open_web_interfaceD

Open web visualization interface

Inputs: port.

remove_dependency_view_edgeB

Remove a dependency edge from a dependency planning view. Returns summary plus changed ids by default; set verbose=true for full data.

Inputs: edgeId (required), viewId (required), projectId (required), verbose.

remove_task_from_dependency_viewA

Remove a task node from a dependency planning view. Connected edges are removed too. Returns summary plus changed ids by default; set verbose=true for full data.

Inputs: taskId (required), viewId (required), projectId (required), verbose.

update_dependency_viewA

Update dependency planning view metadata. Returns summary by default; set verbose=true for full data.

Inputs: viewId (required), projectId (required), name, verbose, +2 more.

update_dependency_view_edgeA

Update the direction of a dependency edge inside a dependency planning view. Returns summary plus changed ids by default; set verbose=true for full data.

Inputs: edgeId (required), viewId (required), projectId (required), verbose, +2 more.

update_dependency_view_nodeA

Update a task node layout or note inside a dependency planning view. Returns summary plus changed ids by default; set verbose=true for full data.

Inputs: taskId (required), viewId (required), projectId (required), x, +4 more.

update_projectB

Update an existing project. Returns summary by default; set verbose=true for full data.

Inputs: projectId (required), name, status, verbose, +4 more.

update_tagC

Update an existing tag

Inputs: tagId (required), projectId (required), name, color, +1 more.

update_taskA

Update an existing task. tags must be existing tag IDs from the same project. Returns summary by default; set verbose=true for full data.

Inputs: taskId (required), projectId (required), tags, title, +6 more.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

    TDQS

    B3.2/5.0

    Scored across 31 tools

    Disambiguation4/5

    Most tools are clearly distinct in action and resource. A few pairs like update_task vs update_dependency_view_node could be confused based on names, but descriptions clarify the difference. Overall, the tool set is well-differentiated.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun snake_case pattern, including batch_ and *_by_tag conventions. The naming style is uniform and predictable.

    Tool Count2/5

    At 31 tools, the server exceeds the 25+ threshold, which feels heavy even for a broad roadmap scope. While each tool has a purpose, the count could be streamlined by consolidating some batch operations.

    Completeness4/5

    The server provides full CRUD for projects, tasks, tags, and dependency views, plus analysis and web UI control. Minor gaps like a missing get_tag or project-level task reassignment exist, but they are not critical for roadmap workflows.

    Maintenance

    ActivityInactive
    ResponsivenessOutdated data

    Related MCP Connectors

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    • F
      license
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      Enables AI assistants to manage a local-first Kanban board with Azure DevOps-style workflow rules, including task creation, status updates, subtask breakdown, full-text search, daily summaries, and next-task suggestions.
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      Enables AI agents to create, query, update, claim, hand off, and complete tasks on a local SQLite-backed, project-namespaced kanban board through stdio MCP tools, including filtering for ready/blocked/stale work and exchanging task attachments. It also lets agents list projects and manage statuses, ownership, and evidence without any server or accounts.
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