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Al Context Create

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javiarmesto
al-context-create

Generate or update context.md file documenting project structure, architecture, and key patterns for AI assistants and developers. ALDC workflow (Copilot prompt al-context.create); invoke explicitly.

Overview

Publisherjaviarmesto
RepositoryALDC-AL-Development-Collection
Skill nameal-context-create
Stars
115
Forks
37
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 javiarmesto on GitHub. Read the source before you install it.

Installation

Install the Al Context Create 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.
    https://github.com/javiarmesto/ALDC-AL-Development-Collection/tree/main/.claude/skills/al-context-create
  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/javiarmesto/ALDC-AL-Development-Collection.git /tmp/ALDC-AL-Development-Collection
mkdir -p .claude/skills
cp -r /tmp/ALDC-AL-Development-Collection/.claude/skills/al-context-create .claude/skills/al-context-create
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Al Context Create 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 Al Context Create 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 Al Context Create 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.

Claude Code adapter — generated by scripts/sync-plugin-support.js, do not edit. Canonical source: prompts/al-context.create.prompt.md (sha256 4fc888854e259401fcdc12f182116ae8376da9abf1330b60dc298c59ed4e3304). This workflow was written for @workspace use … in GitHub Copilot Chat. Apply these harness mappings and treat everything else as binding:

Copilot surface in the contractClaude Code equivalent
#runSubagent / runSubagent / agents:The Task tool with subagent_type: "aldc:<agent>"; one invocation carries everything inline (subagents are stateless)
#askQuestions / vscode/askQuestionsAskUserQuestion (main session only; a subagent returns its questions in its structured output)
handoffs: entries, and send: false on oneNo equivalent — the gate is yours to keep. In Copilot a handoff is a button the human clicks, and send: false additionally hands them the prompt to review before it is sent; the host supplies the approval. Claude Code delegates through the Task tool, with no click and no review step. So never auto-delegate: present your output, get explicit approval, and only then delegate or route to another role. The handoff's routing is carried by the plugin's role entry skills; its human gate is carried by this rule
@al-architect, @al-spec-agent, @al-conductor, @al-developer, @al-developer-reviewer, @al-triage, @al-presales, @al-agent-builder, @dredd/aldc:architect, /aldc:spec, /aldc:conduct, /aldc:develop, /aldc:review, /aldc:triage, /aldc:presales, /aldc:agent-builder, /aldc:audit (or claude --agent aldc:<agent>)
@workspace use <workflow>/aldc:<workflow> with dots replaced by dashes (al-spec.create -> /aldc:al-spec-create); already rewritten below
${input:Name} prompt variablesTake the value from $ARGUMENTS; ask through AskUserQuestion when missing. Already rewritten below as <Name from $ARGUMENTS>
execute / runInTerminal, AL compilation or symbol restoreDeveloper/Implementer: discovered official AL MCP mcp__al__al_compile / mcp__al__al_build / mcp__al__al_downloadsymbols, or an installed ALTool/AL-Go runner through Bash. Use the correct App/Test project; unavailable capabilities are never simulated. Publishing retains its separate human/CI gate and is not granted by this adapter
edit, read/readFile, search, #codebaseEdit/Write, Read, Grep/Glob
#changes, changes, search/changesRead-only git status / git diff through Bash only where granted; otherwise read the caller-supplied diff artifact or return the missing evidence request
read/problems, al_get_diagnostics, #testFailureDiscovered mcp__al__al_getdiagnostics for the explicit project, or actual compiler/test output. Diagnostics are not evidence of a fresh compile or executed tests. No result: record not-run / unavailable
al-symbols-mcp/*, upstash/context7/*, microsoft-learn/*, microsoft-docs/*Tools named mcp__al-symbols-mcp__*, mcp__context7__*, mcp__microsoft-docs__* (or the mcp__plugin_aldc_… form). A server that is not loaded is unavailable; do not simulate it
sshadowsdk.al-lsp-for-agents/*, #usages, semantic definition/reference queriesClaude LSP with the existing AL LSP for Agents companion; discover the actual operations and project context first. VS Code tool identifiers are not Claude tool names
ms-dynamics-smb.al/*, vscode.mermaid-chat-features/*VS Code tool identifiers do not exist here. Use only a separately discovered Claude capability; never rename community tools as Microsoft tools
vscode/memory, vscode/*Not available; keep state in the canonical .claude/plans/ artifacts of the project
todoTodoWrite for in-session tracking; durable state stays in .claude/plans/
"load skill-x"The Skill tool (aldc:<skill-name>) or read ${CLAUDE_PROJECT_DIR}/.claude/skills/<skill-name>/SKILL.md
.github/instructions/*.instructions.md (applyTo)${CLAUDE_PROJECT_DIR}/.claude/rules/*.md (paths:); /aldc:al-initialize copies them to the project's .claude/rules/ for auto-apply in the main session; inject inline for subagents exactly as the contract says
.github/skills/, .github/plans/…, docs/templates/${CLAUDE_PROJECT_DIR}/.claude/skills/, .claude/plans/… (project-owned, aldc.yaml -> plans.root), ${CLAUDE_PROJECT_DIR}/claude-plugin/docs/templates/; already rewritten below
python … runtime helpers, --aldc-rootPaths already point at ${CLAUDE_PLUGIN_ROOT}; use python or python3, whichever exists (stdlib only)
aldc.yaml${CLAUDE_PROJECT_DIR}/aldc.yaml when the project has one, otherwise ${CLAUDE_PROJECT_DIR}/claude-plugin/aldc.yaml

Read ${CLAUDE_PROJECT_DIR}/claude-plugin/docs/claude-al-tooling.md for this surface’s LSP/MCP bindings, then ${CLAUDE_PROJECT_DIR}/.claude/skills/skill-migrate/references/cli-al-tools.md for the shared role/evidence contract. The Claude guide supersedes older capability-availability examples, never role responsibilities or human gates.

AL Context File Generator

Generate a comprehensive context.md file that serves as the master context document for AI assistants and developers working on this AL/Business Central project.

Purpose

The context.md file provides:

  • Project Overview: What this extension does and its business purpose
  • Architecture Snapshot: How the code is organized and key patterns used
  • Critical Decisions: Important architectural choices and their rationale
  • Integration Points: Dependencies, events, APIs exposed/consumed
  • Quick Navigation: Where to find specific functionality

This enables AI assistants to load complete project context quickly and make informed suggestions.

Execution Steps

1. Analyze Project Structure

Load project metadata:

powershell
# Get app.json configuration
@read_file app.json

# Understand dependencies
@al_get_package_dependencies

# Map directory structure
@list_dir src/

Identify key patterns:

powershell
# Find all table extensions
@search "tableextension" *.al

# Find all page extensions
@search "pageextension" *.al

# Find event subscribers
@search "EventSubscriber" *.al

# Find published integration events
@search "IntegrationEvent" *.al

# Find API pages
@search "APIPublisher\|APIVersion" *.al

2. Analyze Business Domain

Understand what the extension does:

  • Read README.md if exists
  • Analyze table/page names to understand business entities
  • Check codeunit names for business processes
  • Review comments and XML docs for business rules

Key questions to answer:

  • What business problem does this solve?
  • Who are the end users?
  • What standard BC functionality does it extend?
  • What industry/vertical is this for (if applicable)?

3. Document Architecture Patterns

Identify and document:

  • Organization Strategy: Feature-based vs object-type folders?
  • Naming Conventions: Prefixes, suffixes, patterns used
  • Extension Patterns: How are standard objects extended?
  • Event Usage: Subscriber patterns, custom events published
  • Data Model: Key tables and their relationships
  • Processing Logic: Main codeunits and their responsibilities
  • UI Structure: Page organization and user flows

4. Map Integration Points

Document:

  • Dependencies: What other extensions are required?
  • Events Subscribed: Which standard BC events are hooked?
  • Events Published: What integration events does this extension provide?
  • APIs: REST/OData endpoints exposed
  • External Integrations: External systems connected (if any)
  • Web Services: SOAP services published (if any)

5. Capture Critical Decisions

Document key architectural choices:

  • Why certain tables are structured in specific ways
  • Why specific event patterns were chosen
  • Performance optimization decisions
  • Security/permission design rationale
  • Any constraints or limitations to be aware of

6. Generate context.md

Create the file at project root with this structure:

markdown
# Project Context - [Extension Name]

> **Auto-generated**: [Date]  
> **Purpose**: Master context document for AI assistants and developers

## 1. Project Overview

### Business Purpose
[What business problem does this extension solve?]

### Target Users
- [User role 1]: [What they do with this extension]
- [User role 2]: [What they do with this extension]

### Extension Metadata
- **App ID**: [from app.json]
- **Version**: [current version]
- **Publisher**: [publisher name]
- **Platform**: [Business Central version target]
- **License**: [if applicable]

## 2. Architecture Overview

### Organization Strategy
[Describe how code is organized - feature-based folders, naming patterns, etc.]

src/ ├── [Feature1]/ │ ├── Data/ # Tables, table extensions │ ├── Processing/ # Codeunits, business logic │ └── UI/ # Pages, page extensions └── [Feature2]/ └── ...


### Key Design Patterns
- **[Pattern 1]**: [Description and rationale]
- **[Pattern 2]**: [Description and rationale]

### Naming Conventions
- **Tables**: [Pattern, e.g., "Prefix_EntityName"]
- **Pages**: [Pattern]
- **Codeunits**: [Pattern]
- **Fields**: [Pattern]
- **Variables**: [Pattern]

## 3. Data Model

### Core Tables
| Table | Object ID | Purpose | Key Relationships |
|-------|-----------|---------|-------------------|
| [Table 1] | [ID] | [Purpose] | → [Related tables] |
| [Table 2] | [ID] | [Purpose] | → [Related tables] |

### Table Extensions
| Extends | New Fields | Purpose |
|---------|------------|---------|
| [Standard Table] | [Field 1, Field 2] | [Why extended] |

### Key FlowFields
- **[Table].[FlowField]**: [What it calculates and why]

## 4. Processing Logic

### Main Codeunits
| Codeunit | Purpose | Key Methods |
|----------|---------|-------------|
| [Name] | [Responsibility] | [Method1(), Method2()] |

### Business Flows
1. **[Flow Name]** (e.g., "Order Approval Flow")
   - Entry point: [Where it starts]
   - Steps: [Key processing steps]
   - Events: [Events published/subscribed]
   - Output: [What it produces]

## 5. UI Structure

### Main Pages
| Page | Type | Purpose | Extends |
|------|------|---------|---------|
| [Page Name] | Card/List/Document | [Purpose] | [Base page if extension] |

### User Flows
1. **[User Task]**: [Navigation path and steps]

## 6. Integration Points

### Dependencies
```json
[List key dependencies from app.json]

Event Subscribers

EventPublisherPurpose
OnBefore[Action][Standard Codeunit][Why subscribed]

Published Events

EventPurposeWhen to Subscribe
OnBefore[CustomAction][Purpose][Use cases for consumers]

APIs / Web Services

  • [API Name]: [Endpoint, purpose, auth method]

External Systems

  • [System Name]: [Integration type, data exchanged]

7. Critical Decisions & Rationale

Decision 1: [Title]

Problem: [What problem was being solved]
Decision: [What was decided]
Rationale: [Why this approach]
Trade-offs: [What was given up]

Decision 2: [Title]

[Same structure]

8. Performance Considerations

  • [Optimization 1]: [Description, where implemented]
  • [Optimization 2]: [Description, where implemented]

Known Bottlenecks

  • [Area]: [Description and mitigation strategy]

9. Security & Permissions

Permission Sets

  • [Permission Set]: [Purpose, scope]

Data Security

  • [How sensitive data is protected]

10. Testing Strategy

Test Coverage

  • Unit tests: [Scope]
  • Integration tests: [Scope]
  • UI tests: [Scope if any]

Test Data

  • [How test data is generated/managed]

11. Quick Navigation Guide

To Find...

  • Customer-related logic: src/[FeatureFolder]/
  • Posting logic: src/[ProcessingFolder]/
  • API endpoints: src/[APIFolder]/
  • Event subscribers: Search for [EventSubscriber]

Common Tasks

  • Adding a new field: [Process/pattern to follow]
  • Subscribing to events: [Pattern/location]
  • Creating API endpoint: [Pattern/location]

12. Known Limitations

  • [Limitation 1]: [Description and workaround if any]
  • [Limitation 2]: [Description and workaround if any]

13. Future Roadmap

  • Planned Features: [If documented]
  • Deprecations: [Anything being phased out]

14. Development Guidelines

Before Making Changes

  1. [Guideline 1]
  2. [Guideline 2]

Code Review Checklist

  • Follows naming conventions
  • XML documentation added
  • Events used instead of modifications
  • Permission sets updated
  • Tests added/updated

15. Useful Commands

powershell
# Build project
al_build

# Download symbols
al_downloadsymbols

# Run tests
@workspace /al-test

# Generate permissions
al_generatepermissionset

16. References

  • Documentation: [Link to detailed docs if exists]
  • Wiki: [Link to wiki if exists]
  • Related Extensions: [Dependencies or companion extensions]

Maintenance: Update this file when:

  • Major architectural changes occur
  • New features/modules are added
  • Integration points change
  • Critical decisions are made

Usage: AI assistants should load this file first when providing assistance on this project.


### 7. Validation Gates

**Before finalizing:**
- ✅ File is under 500 lines for quick loading
- ✅ All sections have actual content (remove empty sections)
- ✅ Links to code examples are accurate
- ✅ Metadata from app.json is correct
- ✅ Architecture diagrams are clear
- ✅ Navigation paths are tested

### 8. Placement & Integration

**Where to create:**
- Place `context.md` at project root (next to app.json)
- If multiple projects, create in each project root

**Git configuration:**
```gitignore
# Add to .gitignore if context contains sensitive info:
# context.md

README integration: Update README.md to reference context.md:

markdown
## For AI Assistants
See [context.md](./context.md) for complete project context.

Output Format

Deliver:

  1. ✅ Complete context.md file at project root
  2. ✅ Summary of what was documented
  3. ✅ List of any sections that need manual review/input
  4. ✅ Recommendation on update frequency

Key Principles

  • Concise but Complete: Include everything AI needs, nothing it doesn't
  • Code-Focused: Link to actual code, not just describe
  • Living Document: Easy to update as project evolves
  • Quick Load: Optimized for AI context window efficiency
  • Self-Contained: Should make sense without external docs

Success Criteria

A successful context.md enables:

  • ✅ New AI assistant can understand project in <2 minutes
  • ✅ Developers can orient themselves quickly
  • ✅ Architectural decisions are clear and justified
  • ✅ Navigation to specific functionality is straightforward
  • ✅ Integration points are well-documented

Frequently asked questions

What does the Al Context Create AI skill do?

Generate or update context.md file documenting project structure, architecture, and key patterns for AI assistants and developers. ALDC workflow (Copilot prompt al-context.create); invoke explicitly.

Why use Al Context Create on TypingMind?

Because you install it once and use it with any model. Al Context Create 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 Al Context Create in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/javiarmesto/ALDC-AL-Development-Collection/tree/main/.claude/skills/al-context-create. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Al Context Create?

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 Al Context Create?

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

Is the Al Context Create AI skill free?

Yes. It is published on GitHub by javiarmesto 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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