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CodeStory

A local code map your coding agent can trust.

License: Apache-2.0 Rust 2024

CodeStory gives coding agents a durable understanding of the repository in front of them: files, symbols, call paths, routes, snippets, and search evidence. Answers stay tied to source locations, and incomplete coverage is reported as a gap instead of being filled with guesses.

flowchart LR
    Repo["your repository"] --> Map["local code map"]
    Question["your question"] --> Agent["coding agent"]
    Map --> Agent
    Agent --> Answer["cited answer, change plan, or review context"]
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The released executable includes CodeRankEmbed Q8 and its accelerator engine. There is no service to start, model to download, port to manage, or retrieval setup to approve. Source, indexes, and queries stay local by default.

What it adds

  • Repository grounding: a compact map of the checkout, its languages, components, and important paths.
  • Symbol and impact navigation: definitions, callers, references, trails, routes, and likely tests without repeated whole-tree scans.
  • Broad retrieval: lexical, semantic, graph, and SCIP evidence combined into cited search results and answer packets.
  • Visible limits: stale, partial, or incoherent evidence fails closed instead of looking complete.

Pick your host

Host Start here
Codex Codex guide — the recommended first install
Cursor Cursor guide
Claude Code Claude Code guide
GitHub Copilot Copilot guide

Capability comparison, day-1 checklist, and shared prompts: User guides.

Quick start

  1. Open the guide for your host and install CodeStory once.
  2. Start a fresh agent session in the repository you want to understand.
  3. Ask an ordinary code question.

That is the normal setup. The first relevant call builds the local map. The first broad question also initializes the embedded model and prepares semantic search. If it needs more than one foreground turn, the agent retries the same call; there is no separate setup or approval flow.

One host process can work across several repositories. Their indexes stay isolated while they share one warm embedding engine:

flowchart LR
    Host["one agent host"] --> A["runtime: repository A"]
    Host --> B["runtime: repository B"]
    A --> CacheA["private index A"]
    B --> CacheB["private index B"]
    A --> Engine["one warm CodeRankEmbed engine"]
    B --> Engine
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Something blocked? Troubleshooting.

Platform support

Platform Release support
macOS 15+ on Apple Silicon Supported with Metal
Windows x64 Supported with Vulkan
Linux x64 Supported with Vulkan
CPU-only Windows and Linux Unsupported
Intel Mac Unsupported
Windows ARM Unsupported

Example prompts

Use your project's symbols and paths:

Find ownership

Where is [Feature] defined, who calls it, and which files should I read first?

Plan a change

I am changing [path/to/file]. What symbols are affected and what tests should I run first?

Understand a subsystem

How does [subsystem] work? Cite concrete files and flag gaps if coverage is incomplete.

More shapes and host-specific invocation: User guides.

Surfaces, host differences, and platform support: User guides.

Documentation

If you want to... Read
Install and use CodeStory User guides
Know when to trust agent output Trust and readiness
Repair a blocked session Troubleshooting
Run CLI repair or debug CLI reference
Change CodeStory itself Contributor setup
Verify a claim or PR Testing matrix

Full routing: docs/README.md.

Evaluation

Scope: The language-expansion holdout proves token and wall-time reduction on 18 pinned public OSS tasks when agents use CodeStory instead of re-reading the tree. It does not prove equal quality for every language, every repo size, or your private checkout. For day-to-day limits, see What to expect.

Language expansion holdout (18 tasks)

Broader public-repo evidence uses the language-support-ab manifest across 18 pinned OSS packages. Latest recorded suite totals:

Metric Without With Change
Context tokens 9,692,559 5,514,580 -43%
Repeat-task wall time 7,943s 4,343s -45%
Tool calls 475 60 -87%
Direct source reads 417 0 -100%

Per-task medians, ranges, reproduction commands, and boundary notes: language-expansion holdout stats.

License

Apache-2.0. See LICENSE.

About

CodeStory is a codebase grounding engine that preindexes code into a knowledge graph and enriches it with semantic context. Paired with coding agents, it results in fewer tokens, fewer tool calls, and remains 100% local.

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