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Documentation Index

Fetch the complete documentation index at: https://docs.joggr.ai/llms.txt

Use this file to discover all available pages before exploring further.

Context is everything an agent knows before it starts. The more accurate and relevant it is, the better the output. Joggr organizes context into three layers — each scoped by where the information lives and what it’s for.

Repo Context

AI instructions, AI rules, and internal docs. Shapes how agents behave within your codebase.

Org Context

Internal knowledge from Jira, Slack, and Confluence — delivered via a single MCP endpoint backed by a knowledge graph, not a flood of raw context.

External Context

External docs for the APIs, frameworks, and services your code depends on.

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How the layers work together

Repo Context shapes how the agent works: your conventions, architecture, and rules applied to every session. jog init generates your AI instructions and rules. jog docs generates your internal docs. Org Context tells the agent what it’s doing: the requirements, decisions, and discussions behind a specific task. jog context connects your internal sources — Jira, Slack, Confluence — and Joggr delivers them through a single MCP endpoint backed by a knowledge graph, surfacing only what’s relevant to the current task and only what you already have access to. External Context tells the agent about the world: the APIs, frameworks, and services your code depends on. jog context connects public docs alongside your internal ones. jog drift detects when your repo context goes stale before it misleads an agent.