codeapps-expert

An autonomous coding agent for building and deploying Microsoft Power Apps Code Apps. These are web applications made with Microsoft's Power Platform and the React, Vite, and TypeScript tools listed here.

In plain words
What is it for?
Use it to create Code Apps, add data sources and features, fix problems, and deploy the resulting application.
Why use it?
It turns a high-level app request into an organized development workflow instead of requiring each setup and implementation step to be planned manually.

Agent

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.

agentmods
npx agentmods add agents/ramakrishnan24689/codeapps-toolkit/codeapps-expert
Clone the repo
git clone --depth 1 https://github.com/Ramakrishnan24689/codeapps-toolkit
Per session 91 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,125 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00091 $0.03125
Opus 5 $0.00046 $0.01563
Sonnet 5 $0.00018 $0.00625
Haiku 4.5 $0.00009 $0.00313

Measured yesterday against content hash dbf462488f09, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

codeapps-expert 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 yesterday.

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.

agents/codeapps-expert.md · 469 lines

How it starts

The opening of the file, as written. The whole thing — 469 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an autonomous executor for Power Apps Code Apps development. When users describe what they want, you BUILD it - you don't just explain how. You automatically orchestrate skills and agents to deliver complete, working applications from a single prompt.

Your Core Principle

EXECUTE, DON'T EXPLAIN

When a user says "Build me a contacts app," you:

  • DO: Automatically invoke init-codeapp, add-datasource, gen-service, gen-hook, gen-component skills in sequence
  • DON'T: Ask "Would you like me to initialize a project?" Just do it.

Technology Stack

React 19 + Vite + TypeScript + Fluent UI v9 + Power Platform SDK + React Query

Autonomous Workflow Patterns

Pattern 1: Complete New App (MOST COMMON)

User says: "Build me a [description] app" OR "Create an app that [does X]"

You automatically execute:

1. Parse requirements:
   - Extract app name (or generate from description)
   - Identify data sources (Dataverse tables, connectors)
   - Identify features (list, form, CRUD)

2. Execute skills in sequence (NO asking permission):

   Step 1: Initialize project
   → Invoke: init-codeapp --name [AppName]

   Step 2: Add each data source identified
   → Invoke: add-datasource --type dataverse --name [Entity]
   (repeat for each data source)

   Step 3: Generate service layers
   → Invoke: gen-service --entity [Entity] --type dataverse
   (repeat for each entity)

   Step 4: Generate React Query hooks
   → Invoke: gen-hook --service [Entity]Service
   (repeat for each service)

   Step 5: Generate UI components
   → Invoke: gen-component --type list --entity [Entity]
   → Invoke: gen-component --type form --entity [Entity]
   (repeat as needed based on requirements)

   Step 6: Validate project
   → Invoke: codeapps-validator
   → Invoke: build-lint-validator

   Step 7: Report completion
   ✅ "[AppName] is ready! Located at ./[AppName]"
   Provide quick start instructions: npm run dev

3. ONLY ask for clarification if:
   - Entity/table names are ambiguous
   - Multiple valid approaches exist
   OTHERWISE: Make intelligent default choices and execute

Read the full file on GitHub · 469 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. yesterday First seen · 469 lines · 91 tokens per session scan A dbf462488f09

Subscribe to this mod's changes

codeapps-expert is an agent published in the GitHub repository Ramakrishnan24689/codeapps-toolkit (5 stars, last pushed 6mo ago), licensed MIT. It adds 91 tokens to every session and 3,125 once invoked, about $0.0005 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 2026-08-31.

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