prime-codebase

Original：🇺🇸 English

Translated

Primes the agent with deep codebase understanding by analyzing structure, documentation, and key files. Use when starting work on a codebase, at the beginning of a session, or when you need a fast orientation before planning or implementing. Optionally pulls external task context from Jira issues and Confluence pages first.

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Sourcecoleam00/skills

Added on2026-08-20

NPX Install

npx skill4agent add coleam00/skills prime-codebase

SKILL.md Content

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Prime: Load Project Context

Objective

Build comprehensive understanding of the codebase by analyzing structure, documentation, and key files. If external task references are provided, load them first so the codebase 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:

Call

mcp__atlassian__getAccessibleAtlassianResources

to obtain the

cloudId

.

For each Jira key, call

mcp__atlassian__getJiraIssue

with that

cloudId

, the issue key, and

responseContentFormat: "markdown"

.

Treat the returned issue summary, description, and acceptance criteria as the task context for everything that follows.

If Confluence page ids are provided:

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).

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. Analyze Project Structure

List all tracked files: !

git ls-files

Show directory structure: On Linux, run:

tree -L 3 -I 'node_modules|__pycache__|.git|dist|build'

2. Read Core Documentation

Read CLAUDE.md or similar global rules file
Read README files at project root and major directories
Read any architecture documentation

3. Identify Key Files

Based on the structure, identify and read:

Main entry points (main.py, index.ts, app.py, etc.)
Core configuration files (pyproject.toml, package.json, tsconfig.json)
Key model/schema definitions
Important service or controller files

4. Understand Current State

Check recent activity: !

git log -10 --oneline

Check current branch and status: !

git status

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

Project Overview

Purpose and type of application
Primary technologies and frameworks
Current version/state

Architecture

Overall structure and organization
Key architectural patterns identified
Important directories and their purposes

Tech Stack

Languages and versions
Frameworks and major libraries
Build tools and package managers
Testing frameworks

Core Principles

Code style and conventions observed
Documentation standards
Testing approach

Current State

Active branch
Recent changes or development focus
Any immediate observations or concerns

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