Context engineering concepts

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Agents behave inconsistently in production when their context is poorly managed. Context is the information an agent relies on to act, such as system instructions, tool definitions, and reference material. Context engineering is the practice of building and optimizing that context to improve agent performance and capabilities. This page covers the core concepts of context engineering in LangSmith: skills, agents, the Context Hub, versioning, and sharing.

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Skills

A skill is a versioned repo in the Context Hub that packages a reusable capability an agent can invoke. Skill repos usually contain: Common files:

• SKILL.md in the root directory for instructions and usage guidance.
• Optional supporting files such as references, templates, and schemas.

Examples include email formatting, code review, and web research.

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Agents

An agent is an AI system that completes tasks end to end using tools, skills, and subagents. An agent repo packages its configuration, including high-level instructions, linked skills and subagents, and tool configuration. Agent repos usually contain: Common files:

• AGENTS.md for system prompt and operating instructions.
• Optional files such as tools.json and linked agents/* or skills/* entries.

Examples include an email assistant, coding copilot, or customer support agent.

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Choose between skills and agents

Skills are reusable context modules. Agent repos are top-level bundles that define how an agent should operate.

• Use skills for reusable instructions, policies, or examples shared across agents.
• Use agent repos for one agent’s operating instructions, tools, and linked dependencies.

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Linked repos

Context Hub commits support three entry types in files:

• file: inline file content.
• agent: link to another agent repo.
• skill: link to another skill repo.

When a linked agent or skill repo gets a new commit, LangSmith propagates that update to parent repos that reference it.

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Context Hub vs. store backend

Context in LangSmith can be managed by two different backends: the Context Hub and a store backend. They serve different purposes, and most agents use both. The Context Hub is your agents’ long-term context store. It tracks every change as a commit and supports versioning, sharing, and continuous improvement. A store backend is built for runtime state. It holds the information an agent accumulates while running: memories, conversation history, user preferences, learned facts, and other data that evolves per session or per user.

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Versioning

Every change to a repo in the Context Hub creates a new commit. Commits are immutable, browsable, and comparable, so you can:

• See exactly what changed between two versions of an agent.
• Revert to any prior commit if a change regresses behavior.
• Tag important commits (for example, the commit you shipped on a specific date) for easy reference.
• Promote a commit to an environment like Staging or Production so downstream agents pull a stable version rather than the latest edit.

If this workflow looks familiar, that is intentional: Context Hub brings the same discipline to agent instructions that Git brings to code.

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Sharing and permissions

The Context Hub is designed for teams. Every repo lives in a workspace, and access depends on workspace permissions plus repo visibility:

• Private repos are visible only inside the workspace.
• Public repos can be discovered and pulled by anyone.
• Creating commits, adding tags, and promoting environments requires update access in the workspace.

Workspace-level sharing and visibility controls make the Hub a natural place to collaborate on agents and skills, and improve them over time.

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Next steps

• Use the Context Hub to create your first skill or agent.

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