Prime Frontend: Load Frontend Context

SkillProductivity

Primes the agent with focused understanding of the frontend portion of the codebase — components, routing, state management, and styling — without loading unrelated backend code. Use at the start of a session when the work is scoped to UI or client-side features. Optionally pulls external task context from Jira issues and Confluence pages first.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Prime Frontend: Load Frontend Context skill

What this skill tells your AI

The instructions your AI receives, as published by coleam00/ai-native-starter-pack in .claude/skills/prime-frontend/SKILL.md and read by ahel’s review.

Objective

Build targeted understanding of the frontend codebase by analyzing its structure, components, and conventions. Loading only frontend context keeps the context window light on complex full-stack codebases. If external task references are provided, load them first so the analysis is anchored to the actual work.

Scope discipline: Limit all file reads to the frontend root and its dependencies. Do NOT load the entire codebase — on large repos this exhausts the context window before any useful work is done.

Process

Step 0: Load External Context

Run this step BEFORE the codebase analysis. It accepts optional arguments: [jira-issue-keys] [confluence-page-ids].

  • Jira keys may be a single key (PROJ-12) or comma-separated (PROJ-12,PROJ-13).
  • Confluence page ids are numeric page ids.

If Jira issue keys are provided:

  1. Call mcp__atlassian__getAccessibleAtlassianResources to obtain the cloudId.
  2. For each Jira key, call mcp__atlassian__getJiraIssue with that cloudId, the issue key, and responseContentFormat: "markdown".
  3. Treat the returned issue summary, description, and acceptance criteria as the task context for everything that follows.

If Confluence page ids are provided:

  1. Call mcp__atlassian__getConfluencePage for each page id with contentFormat: "markdown" (use the cloudId from above, fetching it via mcp__atlassian__getAccessibleAtlassianResources if it was not already retrieved).
  2. Treat the returned page content as supporting context (specs, design docs, requirements).

If no arguments are provided: Skip this step entirely and proceed to Step 1.

Briefly summarize any external context loaded before continuing — this frames the rest of the priming.

1. Locate the Frontend

List all tracked files to find the frontend root:

!git ls-files

Common frontend roots: frontend/, client/, web/, src/ (when project is frontend-only), app/ (Next.js). Identify the correct root before proceeding.

2. Read Frontend Documentation

  • Read CLAUDE.md or similar global rules file (for project-wide conventions)
  • Read any README inside the frontend root
  • Read .claude/references/frontend-component-best-practices.md if it exists — it contains project-specific component conventions

3. Identify Key Frontend Files

Based on the structure, read:

  • Main entry point (main.tsx, index.tsx, app/layout.tsx, pages/_app.tsx, etc.)
  • Routing configuration (router.tsx, routes.ts, app/ directory for Next.js)
  • Global state setup (store, context providers)
  • Shared component library root (components/, ui/)
  • Core configuration (package.json, tsconfig.json, vite.config.ts, next.config.ts)
  • One or two representative feature components to internalize the established patterns

Skip files outside the frontend root unless they define a shared type or contract the frontend depends on.

4. Understand Current Frontend State

Check recent frontend-relevant activity:

!git log -10 --oneline

!git status

Note any open changes in the frontend directory.

Output Report

Provide a concise summary covering:

External Task Context (if loaded)

  • Jira issue(s): key, title, one-line goal, acceptance criteria
  • Confluence page(s): title and what they specify

Frontend Overview

  • Framework and major libraries (React, Vue, Next.js, Tailwind, etc.)
  • Component patterns observed (atomic design, feature folders, etc.)
  • State management approach

Directory Map

  • Frontend root and key sub-directories with one-line purpose each

Conventions

  • Naming conventions, file co-location rules
  • Styling approach
  • Testing framework and conventions observed

Current State

  • Active branch, recent frontend changes
  • Any immediate concerns (missing types, deprecated patterns, etc.)

Make this summary easy to scan - use bullet points and clear headers.

Signals

GitHub stars
69
Forks
23
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
prime-frontend
Source
github.com/coleam00/ai-native-starter-pack