Prime Backend: Load Backend Context

Objective

Build targeted understanding of the backend codebase by analyzing its structure, routes, services, and data layer. Loading only backend 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 backend 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 Backend

List all tracked files to find the backend root:

!git ls-files

Common backend roots: backend/, server/, api/, app/ (FastAPI/Django), src/ (when project is backend-only). Identify the correct root before proceeding.

2. Read Backend Documentation

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

3. Identify Key Backend Files

Based on the structure, read:

• Main entry point (main.py, app.py, server.ts, index.ts, etc.)
• Route registration / router index (routes/, api/, routers/)
• Core configuration (pyproject.toml, package.json, tsconfig.json)
• Database configuration and ORM setup (database.py, db.ts, alembic.ini)
• Core data models or schemas (models/, schemas/)
• One or two representative feature slices (route + service + model) to internalize established patterns
• Middleware and dependency injection setup

Skip files outside the backend root unless they define a shared type or contract the backend exposes.

4. Understand Current Backend State

Check recent backend-relevant activity:

!git log -10 --oneline

!git status

Note any open migrations, pending schema changes, or in-progress API changes.

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

Backend Overview

• Framework and major libraries (FastAPI, Django, Express, NestJS, etc.)
• Language and runtime version
• Database and ORM (PostgreSQL + SQLAlchemy, MongoDB + Mongoose, etc.)

Directory Map

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

Architecture Patterns

• How routes, services, and data access are layered
• Dependency injection or middleware patterns observed
• Error handling approach

Conventions

• Naming conventions, module organization
• Migration tooling and current migration state
• Testing framework and conventions observed

Current State

• Active branch, recent backend changes
• Any pending migrations or schema changes
• Any immediate concerns (missing validation, unhandled errors, etc.)

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