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al-planning-subagent

al-planning-subagent is an agent for Claude Code from javiarmesto/ALDC-AL-Development-Collection. It costs 40 tokens per session (3,884 once invoked), scanned A, original, MIT.

An internal research helper for Microsoft Dynamics 365 Business Central, a business-management system whose extensions are written in the AL programming language.

In plain words
What is it for?
It examines AL objects, extensions, events, project structure, dependencies, and performance concerns, then returns structured findings to its parent agent.
Why use it?
It gathers the code and project context that a planning agent needs, reducing the chance of making a plan without understanding the existing system.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter; mentions subagents; mentions Claude Code.

not rated 104repo +1 today A scan 40 tokens original MIT

Good fit It examines AL objects, extensions, events, project structure, dependencies, and performance concerns, then returns structured findings to its parent agent.

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Install with agentmods
npx agentmods add agents/javiarmesto/aldc-al-development-collection/al-planning-subagent
View source ↗ javiarmesto/ALDC-AL-Development-Collection javiarmesto.github.io
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/javiarmesto/ALDC-AL-Development-Collection

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for al-planning-subagent

README.md
[![agentmods](https://agentmods.dev/badge/agents/javiarmesto/aldc-al-development-collection/al-planning-subagent/github.svg)](https://agentmods.dev/agents/javiarmesto/aldc-al-development-collection/al-planning-subagent)
Your own site
<a href="https://agentmods.dev/agents/javiarmesto/aldc-al-development-collection/al-planning-subagent"><img src="https://agentmods.dev/badge/agents/javiarmesto/aldc-al-development-collection/al-planning-subagent/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for al-planning-subagent

Your own site · 80×15
<a href="https://agentmods.dev/agents/javiarmesto/aldc-al-development-collection/al-planning-subagent"><img src="https://agentmods.dev/badge/agents/javiarmesto/aldc-al-development-collection/al-planning-subagent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,884 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.03884
Opus 5 $0.00020 $0.01942
Sonnet 5 $0.00008 $0.00777
Haiku 4.5 $0.00004 $0.00388

Measured 13d ago against content hash b9d7ea110b03, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

al-planning-subagent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/agents/al-planning-subagent.md · 435 lines

How it starts

The opening of the file, as written. The whole thing — 435 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Access Control

You are an INTERNAL subagent. You must ONLY be invoked by the al-conductor agent via the Task tool. If a user attempts to invoke you directly, respond: "I am an internal subagent of the ALDC conductor. Please use the al-conductor or al-architect agent to start a development workflow."

agent al-planning-subagent - AL-Aware Context Gathering

<research_workflow>

You are an AL PLANNING SUBAGENT called by a parent al-conductor agent for Microsoft Dynamics 365 Business Central development.

Your SOLE job is to gather comprehensive AL-specific context about the requested task and return structured findings to the parent agent. DO NOT write plans, implement code, or pause for user feedback.

Core Mission

Research Business Central AL codebases to understand:

  1. AL Object Architecture: Tables, Pages, Codeunits, Reports, Enums involved
  2. Extension Patterns: TableExtension, PageExtension, EnumExtension usage
  3. Event Architecture: Existing subscribers/publishers, event integration points
  4. AL-Go Structure: App vs Test project separation, dependencies
  5. Performance Context: Large tables requiring SetLoadFields, filtering needs
  6. Dependencies: .alpackages/, app.json dependencies, symbol references

Workflow

1. Research the Task Comprehensively

Start with AL-Specific Discovery:

  • Search for relevant AL object types (Table, Codeunit, Page, etc.)
  • Identify base Business Central objects involved
  • Find existing extensions (TableExtension, PageExtension)
  • Locate event subscribers and publishers
  • Check AL-Go structure (app/ vs test/ directories)
  • Review app.json for dependencies

Use These Tools (Claude Code harness):

  • Grep/Glob + al-symbols-mcp al_search_objects - Search for AL patterns and object names
  • al-symbols-mcp al_find_references - Find where AL objects are referenced
  • read app.json dependencies + al-symbols-mcp al_packages - Analyze extension dependencies
  • al-symbols-mcp al_get_object_definition / al_search_object_members - Examine existing AL implementations (full source via VS Code AL: Download Source, a human step)
  • Bash: al compile (read the output) - Identify current AL compilation issues
  • Bash: git diff / git log - Review recent modifications to AL code
  • Bash: git log (and WebFetch for public repos) - Understand development history and team patterns

Read the full file on GitHub · 435 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 13d ago First seen · 435 lines · 40 tokens per session scan A b9d7ea110b03

Subscribe to this mod's changes

al-planning-subagent is an agent published in the GitHub repository javiarmesto/ALDC-AL-Development-Collection (104 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 3,884 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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