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Website Implementation Plan

Community
luongnv89
website-implementation-plan

Generate phased tasks.md from an approved website PRD, with landing page first, measurable tasks, and collect/create asset tracking. Use for implementation planning. Don't use for coding, design review, unapproved PRDs, or direct deployment.

Overview

Publisherluongnv89
Repositoryskills
Skill namewebsite-implementation-plan
Stars
124
Forks
18
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by luongnv89 on GitHub. Read the source before you install it.

Installation

Install the Website Implementation Plan AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/luongnv89/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/website-cloner/website-implementation-plan .claude/skills/website-implementation-plan
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Website Implementation Plan in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Website Implementation Plan on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Website Implementation Plan is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Website Implementation Plan

Turns an approved improvement proposal (prd.md) into a phased implementation plan. Landing page first, then deeper pages. Asset collection vs. creation tracked. Writes tasks.md after approval.

When to Use

Trigger when the user asks to:

  • Plan the implementation of a website improvement proposal
  • Break down a PRD into phased tasks
  • Create an implementation plan for a site rebuild

Do not use for building or coding — that is Phase 5 (website-builder).

Workflow

1. Read the approved prd.md
2. Identify phases: landing page first, then deeper content
3. For each task: define scope, outputs, acceptance criteria
4. Track assets: collect from original vs. create new
5. Assemble into tasks.md
6. Present for review
7. Incorporate edits (loop until approved)
8. Persist tasks.md

Output: tasks.md Structure

Use the tasks.md template below as the only output template. Read only the PRD sections needed for the current phase to preserve the context budget.

markdown
# Implementation Plan: <site name>
**Source PRD:** prd.md
**Date:** <date>

---

## Overview

Brief summary of the implementation approach and phase ordering rationale.

## Phase 1: Landing Page

The landing/home page is built first so it can be shown to potential users early.

### Task 1.1: Project Setup

**Scope:** Initialize Vite + React + shadcn/ui + Tailwind CSS project. Configure build, base-aware routing/assets, and deterministic GitHub Actions Pages artifact deployment.

**Outputs:** Working project scaffold, base-aware Vite configuration, and `.github/workflows/deploy-pages.yml`.

**Acceptance Criteria:**
- `npm run dev` starts a local dev server
- `npm run build` produces `dist/index.html`
- `vite.config.*` consumes `VITE_BASE_PATH`; the workflow sets `/` for user/organization Pages and `/<repo>/` for project Pages
- Internal routes and public assets resolve under the configured base; the selected SPA route strategy has a direct-refresh check
- The Pages workflow runs `npm ci` and `npm run build`, uploads exactly `dist/` with `actions/upload-pages-artifact`, and deploys it with `actions/deploy-pages`
- Pages source is GitHub Actions, never repository-root, `/docs`, or branch-folder publishing

**Assets Needed:**
- [Collect] Logo, brand colors, brand name from original site
- [Create] Project repository on GitHub

### Task 1.2: Landing Page Layout

**Scope:** Build the hero section, nav, CTA, and footer based on the improvement proposal. Implement the improved layout, not a clone.

**Outputs:** Landing page component with improved structure.

**Acceptance Criteria:**
- Hero section with clear headline, subtext, primary CTA above the fold
- Responsive layout (mobile + desktop)
- Navigation matches the improved structure

**Assets Needed:**
- [Collect] Hero imagery, copy text, brand colors
- [Create] New CTA copy (if improvement proposes different messaging)

---

## Phase 2: Core Pages

Deeper pages beyond the landing page.

### Task 2.1: <Page Name>

**Scope:** ...
**Outputs:** ...
**Acceptance Criteria:** ...
**Assets Needed:**
- [Collect] ...
- [Create] ...

---

Repeat for each task across phases.

## Phase 3: Optimization and Polish

Performance, SEO, and security improvements from the PRD.

### Task 3.1: Performance Optimization

**Scope:** Image optimization, lazy loading, code splitting, font optimization.

**Acceptance Criteria:**
- LCP ≤ target (from prd.md metrics table)
- CLS ≤ target
- Page weight ≤ target

### Task 3.2: SEO Implementation

**Scope:** Meta tags, structured data, heading structure, alt text, canonical URLs.

**Acceptance Criteria:**
- SEO score ≥ target
- All pages have title, meta description, structured data

### Task 3.3: Security Hardening

**Scope:** HTTPS enforcement, security headers, mixed content fixes.

**Acceptance Criteria:**
- All resources loaded over HTTPS
- Key security headers present

## Asset Summary

| Asset | Source | Action |
|-------|--------|--------|
| Logo | Original site | Collect |
| Brand colors | Original site | Collect |
| Hero image | Original site | Collect |
| CTA copy | Improvement proposal | Create |
| New icons | Generated | Create |

## Deployment

1. Include `package-lock.json`, base-aware `vite.config.*`, and `.github/workflows/deploy-pages.yml` in the implementation tasks.
2. Push the approved project to the default branch and configure Repository Settings → Pages → Source as **GitHub Actions**.
3. Require the workflow to build and verify `dist/index.html`, upload exactly `dist/` as the Pages artifact, and deploy that artifact.
4. Verify project Pages at `https://<user>.github.io/<repo>/`; for a `<user>.github.io` repository, verify the root URL instead.

---

*This plan is derived from the approved improvement proposal. Actual task scope may need adjustment during implementation.*

Step 1: Read prd.md

Read file <path-to-prd.md>

If missing, ask for the path. The orchestrator should have produced this in Phase 3.

Step 2: Define Phases

Structure phases so something usable ships early:

PhaseFocusRationale
Phase 1Landing/home pageUsable immediately, can be shown to users
Phase 2Core pagesAbout, features, contact, etc.
Phase 3OptimizationPerformance, SEO, security polish
Phase 4 (optional)Extra featuresNice-to-have improvements

Phase 1 must produce an independently usable landing page.

Step 3: Define Tasks

For each task:

  • Scope: Clear, bounded description of what to build
  • Outputs: Concrete deliverables
  • Acceptance Criteria: Measurable pass/fail conditions
  • Assets Needed: Distinguish [Collect] from [Create]

Tasks should be small enough for a single implementation cycle.

Step 4: Asset Tracking

For every asset referenced in the plan:

  • Mark as [Collect] if it exists on the original site (logos, images, copy, colors)
  • Mark as [Create] if it needs to be newly produced (new icons, rewritten copy, generated images)

Step 5: Write Draft tasks.md

Assemble using the structure above.

Step 6: Present for Review

"Here is the implementation plan. Please:

  1. Approve — save as tasks.md
  2. Edit — specify changes
  3. Regenerate — start over"

Step 7: Incorporate Edits (loop)

If edits requested: update, re-present, repeat until approved.

Do not persist until explicit approval.

Step 8: Persist tasks.md

bash
printf '%s\n' "$TASKS_CONTENT" > "$OUTPUT_PATH"

Default: $PROJECT_DIR/tasks.md or ~/workspace/clones/YYYY_MM_DD_slug/tasks.md.

If $ARGUMENTS includes --output <path>, use that.

Confirm:

tasks.md saved to: <absolute-path>
STATUS: approved

Return Contract

When invoked by the website-cloner umbrella (Phase 4 gate), the orchestrator gates Phase 5 on this skill's outcome. The contract:

OutcomeSignal
approvedtasks.md exists at the resolved output path AND final line of stdout reads STATUS: approved
pendingno tasks.md written; final line reads STATUS: pending (user still iterating)
abortedno tasks.md written; final line reads STATUS: aborted (user declined)

The orchestrator MUST NOT advance to Phase 5 unless the outcome is approved. A standalone invocation may ignore the status line, but the file-existence rule still holds: no approval, no tasks.md.

Acceptance Criteria and Expected Output

Verify the complete plan before requesting approval:

  • Every in-scope PRD requirement maps to at least one numbered task or an explicitly justified exclusion.
  • Phase 1 produces an independently usable landing page; later phases preserve dependency order.
  • Every task has bounded scope, concrete outputs, measurable acceptance criteria, and all required assets classified as [Collect] or [Create].
  • Project setup includes the artifact-based Pages workflow, deterministic Vite base-path behavior, and route/asset checks; no plan publishes Vite output from repository root or /docs.
  • Asset Summary contains every asset named by a task exactly once with a source and action.
  • The expected result is valid markdown at the approved path plus exactly one final STATUS: approved; pending or aborted outcomes write no file.

Step Completion Report

text
◆ Implementation Plan
··································································
  Approved PRD:         √ pass | × fail ([reason])
  Landing page first:  √ pass
  Tasks measurable:    √ pass ([count])
  Assets classified:   √ pass ([collect]/[create])
  User approved:       √ pass | × pending
  tasks.md saved:      √ pass ([absolute path]) | — not approved
  Result:              PASS | BLOCKED | FAIL

Report PASS only when the return contract's file and final status-line conditions both hold.

Edge Cases and Error Handling

FailureBehavior
No prd.md providedAsk for the PRD file path
Invalid PRD formatReport error and ask for valid file
Conflicting PRD requirementsSurface the conflict and ask before task decomposition
No assets requiredInclude an empty Asset Summary and state that no collection or creation is needed
User never approvesKeep looping; do not auto-save

Frequently asked questions

What does the Website Implementation Plan AI skill do?

Generate phased tasks.md from an approved website PRD, with landing page first, measurable tasks, and collect/create asset tracking. Use for implementation planning. Don't use for coding, design review, unapproved PRDs, or direct deployment.

Why use Website Implementation Plan on TypingMind?

Because you install it once and use it with any model. Website Implementation Plan is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Website Implementation Plan in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/luongnv89/skills/tree/main/skills/website-cloner/website-implementation-plan. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Website Implementation Plan?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Website Implementation Plan?

As many as you like. As long as a model supports skills, you can use Website Implementation Plan with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Website Implementation Plan AI skill free?

Yes. It is published on GitHub by luongnv89 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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