prime-backend
Primes the agent with focused understanding of the backend portion of the codebase — API routes, services, data models, and database layer — without loading unrelated frontend code. Use at the start of a session when the work is scoped to API endpoints, business logic, or data access. Optionally pulls external task context from Jira issues and Confluence pages first.
Works with
--- name: prime-backend description: Primes the agent with focused understanding of the backend portion of the codebase — API routes, services, data models, and database layer — without loading unrelated frontend code. Use at the start of a session when the work is scoped to API endpoints, business logic, or data access. Optionally pulls external task context from Jira issues and Confluence pages first. license: MIT --- # 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. ## 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 (`ACC-2`) or comma-separated (`ACC-2,ACC-3`). - 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.**
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