---
title: "What is a context slice?"
description: "A context slice is the minimal subgraph of your codebase that answers one question. Here's how GraphSlice extracts one, and why the boundaries matter."
date: 2026-06-25
tags: [code-graph, context-engineering]
---

"Context slice" is the core noun in GraphSlice, so it deserves a precise
definition: a slice is the **minimal connected subgraph** of your semantic
code graph that is sufficient to answer one question.

## Anatomy of a slice

Every slice has three parts:

### The anchor

The symbol the question is about — a method, a type, an interface, a project.
Anchors are resolved by real symbol identity, not by name matching, so
`Process` on `OrderService` never gets confused with `Process` on
`ImagePipeline`.

### The traversal

From the anchor, GraphSlice walks the edges that the question type calls for:

| Question | Edges walked |
| --- | --- |
| "Who calls this?" | incoming call edges |
| "What breaks if I change this?" | implementations, overrides, references |
| "Trace this dependency" | project + package dependency edges |
| "Show the flow" | call edges, direction of execution |

The traversal is bounded — by depth, by project boundary, or by relevance —
so a hub symbol with ten thousand references doesn't flood the window.

### The rendering

The subgraph is rendered in a form an LLM consumes efficiently: compact,
hierarchical, deduplicated, with file-and-line anchors so the assistant can
jump from structure to source when it needs the actual code.

## What a slice deliberately leaves out

The discipline is in the omissions. A slice does **not** include:

- Method bodies that aren't on the dependency path.
- Symbols that merely live in the same file as something relevant.
- Anything retrieved because it was *textually similar* to the question.

Proximity in a file is an accident of formatting. Proximity in the graph is a
fact about your software.

## Why "minimal" is a feature

It's tempting to pad context "just in case" — but every irrelevant symbol in
the window is a chance for the model to anchor on the wrong thing. Precision
in, precision out. Keeping slices minimal is what keeps token costs flat as
the repository grows: the graph gets bigger, but the answers don't.