adynato-aimake
Integrate with aimake's AI-powered delivery pipeline via MCP. Covers connecting to aimake, using code/docs/kanban tools, understanding the card-based system, and leveraging AI capabilities. Use when building integrations with aimake or using its MCP tools.
Best use case
adynato-aimake is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Integrate with aimake's AI-powered delivery pipeline via MCP. Covers connecting to aimake, using code/docs/kanban tools, understanding the card-based system, and leveraging AI capabilities. Use when building integrations with aimake or using its MCP tools.
Teams using adynato-aimake should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/adynato-aimake/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How adynato-aimake Compares
| Feature / Agent | adynato-aimake | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Integrate with aimake's AI-powered delivery pipeline via MCP. Covers connecting to aimake, using code/docs/kanban tools, understanding the card-based system, and leveraging AI capabilities. Use when building integrations with aimake or using its MCP tools.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# aimake Skill
Use this skill when integrating with aimake via MCP or leveraging its AI-powered delivery tools.
## What is aimake?
aimake is an AI-powered delivery pipeline platform where **cards are the deliverables**, not tickets about work happening elsewhere. The AI drives work forward while humans bring taste and decision-making.
**Key Concepts:**
- **Cards** are atomic, independently deliverable work units
- **Boards** organize cards by type (Product, Engineering, Bugs, Docs)
- **Stages** are quality gates that enforce professional standards
- **Card AI** co-authors deliverables through conversation
## Connecting via MCP
aimake exposes its functionality through MCP (Model Context Protocol).
### Endpoints
```
GET /mcp/manifest # Returns available tool definitions
POST /mcp/tools/:name # Executes a specific tool
```
### Example Connection
```typescript
// Fetch available tools
const manifest = await fetch('https://your-aimake-instance/mcp/manifest');
const tools = await manifest.json();
// Execute a tool
const result = await fetch('https://your-aimake-instance/mcp/tools/search_code_text', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
},
body: JSON.stringify({
query: 'authentication',
project_id: 'proj_123'
})
});
```
## Available MCP Tools
### Code Tools
Search and analyze code in connected repositories.
| Tool | Description | Key Parameters |
|------|-------------|----------------|
| `search_code_semantic` | AI embeddings for conceptual matching | `query`, `project_id` |
| `search_code_text` | Ripgrep-based pattern matching | `query`, `project_id`, `file_pattern` |
| `read_file` | Get file content with line numbers | `path`, `project_id` |
| `list_directory` | Browse repository structure | `path`, `project_id` |
| `get_file_tree` | Complete code structure overview | `project_id` |
**Example: Semantic Code Search**
```json
{
"tool": "search_code_semantic",
"input": {
"query": "how is user authentication handled",
"project_id": "proj_123"
}
}
```
### Documentation Tools
Access and search project documentation.
| Tool | Description | Key Parameters |
|------|-------------|----------------|
| `search_docs` | Full-text search across docs | `query`, `project_id` |
| `get_doc_page` | Retrieve specific page | `page_id`, `project_id` |
| `list_docs` | List all documentation pages | `project_id` |
**Example: Search Documentation**
```json
{
"tool": "search_docs",
"input": {
"query": "API rate limits",
"project_id": "proj_123"
}
}
```
### Kanban Tools
Manage cards and projects in the delivery pipeline.
| Tool | Description | Key Parameters |
|------|-------------|----------------|
| `query_cards` | Search and filter cards | `project_id`, `board`, `stage`, `search` |
| `get_card` | Get card details | `card_id` |
| `update_card_field` | Update a card field | `card_id`, `field`, `value` |
| `move_card_to_stage` | Move card to different stage | `card_id`, `stage` |
| `spawn_cards` | Create new cards | `project_id`, `board`, `cards[]` |
| `get_project` | Get project details | `project_id` |
**Example: Query Cards**
```json
{
"tool": "query_cards",
"input": {
"project_id": "proj_123",
"board": "engineering",
"stage": "in_progress",
"search": "authentication"
}
}
```
**Example: Create Cards**
```json
{
"tool": "spawn_cards",
"input": {
"project_id": "proj_123",
"board": "engineering",
"cards": [
{ "title": "Add OAuth2 support", "stage": "backlog" },
{ "title": "Implement refresh tokens", "stage": "backlog" }
]
}
}
```
## Understanding Boards and Stages
### Board Types
| Board | Purpose | Use For |
|-------|---------|---------|
| **Product** | Specs and requirements | Feature definitions, user stories |
| **Engineering** | Implementation tasks | Code work, technical tasks |
| **Bugs** | Issue tracking | Bug reports, fixes |
| **Docs** | Documentation | Project docs, guides |
### Stage Progression
Cards move through stages as work progresses:
**Product Board:**
```
problemStatement → acceptanceCriteria → technicalReview → ready
```
**Engineering Board:**
```
backlog → in_progress → review → done
```
### Atomicity Rules
Each card should be atomic and independently deliverable:
| Board | What's Atomic |
|-------|---------------|
| Product | One shippable experience ("Welcome screen" not "Onboarding") |
| Engineering | One independently shippable component |
| Bugs | One specific, reproducible problem |
## Working with Card AI
Each card has an AI assistant that helps co-author the deliverable.
### What Card AI Can Do
- Fill in card fields based on conversation
- Detect scope creep and suggest splitting cards
- Validate readiness before stage transitions
- Search code and docs for context
- Break down large work into atomic cards
### Integration Pattern
When building tools that interact with aimake cards:
```typescript
// 1. Get card context
const card = await mcpTool('get_card', { card_id: 'card_123' });
// 2. Search for relevant code
const codeContext = await mcpTool('search_code_semantic', {
query: card.title,
project_id: card.project_id
});
// 3. Update card with findings
await mcpTool('update_card_field', {
card_id: 'card_123',
field: 'technicalNotes',
value: `Relevant files:\n${codeContext.results.map(r => r.path).join('\n')}`
});
```
## Common Integration Patterns
### Triage Agent
Use aimake to analyze and route incoming requests:
```typescript
// 1. Search docs for relevant context
const docs = await mcpTool('search_docs', { query: userRequest, project_id });
// 2. Search code for implementation details
const code = await mcpTool('search_code_semantic', { query: userRequest, project_id });
// 3. Create appropriate card
await mcpTool('spawn_cards', {
project_id,
board: isFeature ? 'product' : 'bugs',
cards: [{ title: summarize(userRequest), stage: 'backlog' }]
});
```
### Context Retrieval
Pull relevant context from aimake for AI conversations:
```typescript
// Get project overview
const project = await mcpTool('get_project', { project_id });
const fileTree = await mcpTool('get_file_tree', { project_id });
const docs = await mcpTool('list_docs', { project_id });
// Search for specific context
const relevantCode = await mcpTool('search_code_text', {
query: 'class UserAuth',
project_id
});
```
### Progress Tracking
Query cards to understand project state:
```typescript
// Get all in-progress work
const activeWork = await mcpTool('query_cards', {
project_id,
stage: 'in_progress'
});
// Get cards related to a feature
const featureCards = await mcpTool('query_cards', {
project_id,
search: 'authentication',
boards: ['product', 'engineering', 'bugs']
});
```
## Tool Response Format
All MCP tools return JSON responses:
```typescript
// Success
{
"success": true,
"data": { /* tool-specific response */ }
}
// Error
{
"success": false,
"error": "Error message"
}
```
### Code Search Response
```typescript
{
"results": [
{
"path": "src/auth/login.ts",
"lines": "45-67",
"content": "...",
"score": 0.92
}
]
}
```
### Card Response
```typescript
{
"id": "card_123",
"title": "Add OAuth2 support",
"board": "engineering",
"stage": "in_progress",
"data": {
"problemStatement": "...",
"acceptanceCriteria": "...",
"technicalNotes": "..."
}
}
```Related Skills
adynato-github
GitHub workflow conventions for Adynato projects. Covers creating PRs with gh CLI, writing thorough descriptions, and using stacked PRs for large deliverables. Use when creating pull requests, managing branches, or breaking down large features.
adynato-seo
Handles SEO requirements for all web content including blogs, landing pages, and documentation. Covers LD+JSON schema.org structured data, internal backlinks strategy, further reading sections, meta tags, and Open Graph. Use when creating or editing any public-facing web content, blog posts, or pages that need search visibility.
adynato-web-api
Web API development conventions for Adynato projects. Covers API routes, middleware, authentication, error handling, validation, and response formats for Next.js and Node.js backends. Use when building or modifying API endpoints, server actions, or backend logic.
adynato-mobile-api
API integration patterns for Adynato mobile apps. Covers data fetching with TanStack Query, authentication flows, offline support, error handling, and optimistic updates in React Native/Expo apps. Use when integrating APIs into mobile applications.
bgo
Automates the complete Blender build-go workflow, from building and packaging your extension/add-on to removing old versions, installing, enabling, and launching Blender for quick testing and iteration.
moai-lang-r
R 4.4+ best practices with testthat 3.2, lintr 3.2, and data analysis patterns.
moai-lang-python
Python 3.13+ development specialist covering FastAPI, Django, async patterns, data science, testing with pytest, and modern Python features. Use when developing Python APIs, web applications, data pipelines, or writing tests.
moai-icons-vector
Vector icon libraries ecosystem guide covering 10+ major libraries with 200K+ icons, including React Icons (35K+), Lucide (1000+), Tabler Icons (5900+), Iconify (200K+), Heroicons, Phosphor, and Radix Icons with implementation patterns, decision trees, and best practices.
moai-foundation-trust
Complete TRUST 4 principles guide covering Test First, Readable, Unified, Secured. Validation methods, enterprise quality gates, metrics, and November 2025 standards. Enterprise v4.0 with 50+ software quality standards references.
moai-foundation-memory
Persistent memory across sessions using MCP Memory Server for user preferences, project context, and learned patterns
moai-foundation-core
MoAI-ADK's foundational principles - TRUST 5, SPEC-First TDD, delegation patterns, token optimization, progressive disclosure, modular architecture, agent catalog, command reference, and execution rules for building AI-powered development workflows
moai-cc-claude-md
Authoring CLAUDE.md Project Instructions. Design project-specific AI guidance, document workflows, define architecture patterns. Use when creating CLAUDE.md files for projects, documenting team standards, or establishing AI collaboration guidelines.