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Notion Spec To Implementation

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Prat011
notion-spec-to-implementation

Turns product or tech specs into concrete Notion tasks that Claude code can implement. Breaks down spec pages into detailed implementation plans with clear tasks, acceptance criteria, and progress tracking to guide development from requirements to completion.

Overview

PublisherPrat011
Repositoryawesome-llm-skills
Skill namenotion-spec-to-implementation
Stars
1.7K
Forks
303
Bundled files
13
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.

  • 13 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Prat011 on GitHub. Read the source before you install it.

Installation

Install the Notion Spec To Implementation 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/Prat011/awesome-llm-skills.git /tmp/awesome-llm-skills
mkdir -p .claude/skills
cp -r /tmp/awesome-llm-skills/notion-spec-to-implementation .claude/skills/notion-spec-to-implementation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Notion Spec To Implementation 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 Notion Spec To Implementation 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 Notion Spec To Implementation 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.

Spec to Implementation

Transforms specifications into actionable implementation plans with progress tracking. Fetches spec documents, extracts requirements, breaks down into tasks, and manages implementation workflow.

Quick Start

When asked to implement a specification:

  1. Find spec: Use Notion:notion-search to locate specification page
  2. Fetch spec: Use Notion:notion-fetch to read specification content
  3. Extract requirements: Parse and structure requirements from spec
  4. Create plan: Use Notion:notion-create-pages for implementation plan
  5. Find task database: Use Notion:notion-search to locate tasks database
  6. Create tasks: Use Notion:notion-create-pages for individual tasks in task database
  7. Track progress: Use Notion:notion-update-page to log progress and update status

Implementation Workflow

Step 1: Find the specification

1. Search for spec:
   - Use Notion:notion-search with spec name or topic
   - Apply filters if needed (e.g., created_date_range, teamspace_id)
   - Look for spec title or keyword matches
   - If not found or ambiguous, ask user for spec URL/ID

Example searches:
- "User Authentication spec"
- "Payment Integration specification"
- "Mobile App Redesign PRD"

Step 2: Fetch and analyze specification

1. Fetch spec page:
   - Use Notion:notion-fetch with spec URL/ID from search results
   - Read full content including requirements, design, constraints

2. Parse specification:
   - Identify functional requirements
   - Note non-functional requirements (performance, security, etc.)
   - Extract acceptance criteria
   - Identify dependencies and blockers

See reference/spec-parsing.md for parsing patterns.

Step 3: Create implementation plan

1. Break down into phases/milestones
2. Identify technical approach
3. List required tasks
4. Estimate effort
5. Identify risks

Use implementation plan template (see [reference/standard-implementation-plan.md](reference/standard-implementation-plan.md) or [reference/quick-implementation-plan.md](reference/quick-implementation-plan.md))

Step 4: Create implementation plan page

Use Notion:notion-create-pages:
- Title: "Implementation Plan: [Feature Name]"
- Content: Structured plan with phases, tasks, timeline
- Link back to original spec
- Add to appropriate location (project page, database)

Step 5: Find task database

1. Search for task database:
   - Use Notion:notion-search to find "Tasks" or "Task Management" database
   - Look for engineering/project task tracking system
   - If not found or ambiguous, ask user for database location

2. Fetch database schema:
   - Use Notion:notion-fetch with database URL/ID
   - Get property names, types, and options
   - Identify correct data source from <data-source> tags
   - Note required properties for new tasks

Step 6: Create implementation tasks

For each task in plan:
1. Create task in task database using Notion:notion-create-pages
2. Use parent: { data_source_id: 'collection://...' }
3. Set properties from schema:
   - Name/Title: Task description
   - Status: To Do
   - Priority: Based on criticality
   - Related Tasks: Link to spec and plan
4. Add implementation details in content

See reference/task-creation.md for task patterns.

Step 7: Begin implementation

1. Update task status to "In Progress"
2. Add initial progress note
3. Document approach and decisions
4. Link relevant resources

Step 8: Track progress

Regular updates:
1. Update task properties (status, progress)
2. Add progress notes with:
   - What's completed
   - Current focus
   - Blockers/issues
3. Update implementation plan with milestone completion
4. Link to related work (PRs, designs, etc.)

See reference/progress-tracking.md for tracking patterns.

Spec Analysis Patterns

Functional Requirements: User stories, feature descriptions, workflows, data requirements, integration points

Non-Functional Requirements: Performance targets, security requirements, scalability needs, availability, compliance

Acceptance Criteria: Testable conditions, user validation points, performance benchmarks, completion definitions

See reference/spec-parsing.md for detailed parsing techniques.

Implementation Plan Structure

Plan includes: Overview → Linked Spec → Requirements Summary → Technical Approach → Implementation Phases (Goal, Tasks checklist, Estimated effort) → Dependencies → Risks & Mitigation → Timeline → Success Criteria

See reference/standard-implementation-plan.md for full plan template.

Task Breakdown Patterns

By Component: Database, API endpoints, frontend components, integration, testing By Feature Slice: Vertical slices (auth flow, data entry, report generation) By Priority: P0 (must have), P1 (important), P2 (nice to have)

Progress Logging

Daily Updates (active work): Add progress note with completed items, current focus, blockers Milestone Updates (major progress): Update plan checkboxes, add milestone summary, adjust timeline Status Changes (task transitions): Update properties (In Progress → In Review → Done), add completion notes, link deliverables

Progress Format: Date heading → Completed → In Progress → Next Steps → Blockers → Notes

See reference/progress-tracking.md for detailed patterns.

Linking Spec to Implementation

Forward Links: Update spec page with "Implementation" section linking to plan and tasks Backward Links: Reference spec in plan and tasks with "Specification" section Bidirectional Traceability: Maintain both directions for easy tracking

Implementation Status Tracking

Plan Status: Update with phase completion (✅ Complete, 🔄 In Progress %, ⏳ Not Started) and overall percentage Task Aggregation: Query task database by plan ID to generate summary (complete, in progress, blocked, not started)

Handling Spec Changes

Detection: Fetch updated spec → compare with plan → identify new requirements → assess impact Propagation: Update plan → create new tasks → update affected tasks → add change note → notify via comments Change Log: Track spec evolution with date, what changed, and impact

Common Patterns

Feature Flag: Backend (behind flag) → Testing → Frontend (flagged) → Internal rollout → External rollout Database Migration: Schema design → Migration script → Staging test → Production migration → Validation API Development: API design → Backend implementation → Testing & docs → Client integration → Deployment

Best Practices

  1. Always link spec and implementation: Maintain bidirectional references
  2. Break down into small tasks: Each task should be completable in 1-2 days
  3. Extract clear acceptance criteria: Know when "done" is done
  4. Identify dependencies early: Note blockers in plan
  5. Update progress regularly: Daily notes for active work
  6. Track changes: Document spec updates and their impact
  7. Use checklists: Visual progress indicators help everyone
  8. Link deliverables: PRs, designs, docs should link back to tasks

Advanced Features

For additional implementation patterns and techniques, see the reference files in reference/.

Common Issues

"Can't find spec": Use Notion:notion-search with spec name/topic, try broader terms, or ask user for URL "Multiple specs found": Ask user which spec to implement or show options "Can't find task database": Search for "Tasks" or "Task Management", or ask user for database location "Spec unclear": Note ambiguities in plan, create clarification tasks "Requirements conflicting": Document conflicts, create decision task "Scope too large": Break into smaller specs/phases

Examples

See examples/ for complete workflows:

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Notion Spec To Implementation AI skill do?

Turns product or tech specs into concrete Notion tasks that Claude code can implement. Breaks down spec pages into detailed implementation plans with clear tasks, acceptance criteria, and progress tracking to guide development from requirements to completion.

Why use Notion Spec To Implementation on TypingMind?

Because you install it once and use it with any model. Notion Spec To Implementation 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 Notion Spec To Implementation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Prat011/awesome-llm-skills/tree/master/notion-spec-to-implementation. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Notion Spec To Implementation?

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 Notion Spec To Implementation?

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

Is the Notion Spec To Implementation AI skill free?

It is published on GitHub by Prat011. Check the repository for licensing terms. 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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