Dekko

io.github.aahlijia由 GitHub 帳號 aahlijia 發布v1.9.0更新於 Oct 24, 2026

Static code map generator: MAP.md + map.json for any repo, plus a Claude Code /map plugin

已驗證STDIO僅桌面知識與記憶開發者工具

概覽

AI 產生的概覽

Dekko 為程式碼倉庫產生靜態程式碼地圖與呼叫圖,讓助理用遠少於讀檔的 token 回答程式庫問題。

可以做什麼
  • 產生倉庫地圖:以 tree-sitter 掃描倉庫,輸出可讀的 MAP.md 與機器可讀的 map.json。
  • 概覽程式庫:取得目錄、熱點與進入點的簡短摘要。
  • 檢視檔案與目錄:不必逐行閱讀即可列出大型檔案或目錄的結構。
  • 追蹤符號:查詢某個函式被誰呼叫、呼叫了誰,以及外部 API 的使用情況。
  • 為某個符號或任務打包上下文。
適用情境
適合助理在大型或不熟悉的倉庫中工作,需要快速掌握全貌、列出檔案大綱或追蹤呼叫關係,又不想花 token 通讀整個檔案時。對小型、自成一體的檔案或 grep 已能輕鬆處理的符號,效益有限。
執行需求
以 stdio 本機程序執行,從 PyPI 安裝(uvx、uv tool install、pip 或 pipx),需要 Python 執行環境。未宣告帳號、API 金鑰或環境變數。更多語言支援需安裝 dekko[all] 附加套件,向量檢索需 dekko[search]。
安裝前請注意
會在本機掃描倉庫原始碼,並在專案中寫入 .dekko/ 目錄(預設被 git 忽略)。選用附加套件會引入額外相依套件。未宣告需要憑證或網路存取。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Dekko,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

[dekko]

[CI] [PyPI] [Downloads] [Python] [License: MIT] [Ruff]

Ever watched your coding agent grep blind through a repo, open three files it didn't need, and burn fifteen thousand tokens just to answer "who calls this function"? That's the problem dekko exists to fix.

[dekko demo: mapping a repo and querying a symbol in seconds]

This demo runs on dekko's own repo (commit 835733c) — clone it and run the same three commands yourself.

dekko is a fast, offline, dependency-free static code map generator and codebase indexer for LLM coding agents. It scans a repository with tree-sitter (no model tokens spent parsing) and writes:

  • MAP.md — a human-readable map: a per-directory overview, an embedded architecture diagram, load-bearing/orchestrator rankings, then every file's functions/methods with signatures, doc lines, and who calls and is called by whom.
  • map.json — the same graph in machine-readable form.

On top of the map, dekko gives an agent a token-cheap way to answer questions like "what does this file contain," "who calls this function," and "what do I need to safely change this" — without reading whole files. It ships as a CLI, a Claude Code /map plugin + MCP server (Model Context Protocol), and works with Cline too.

The result: 10x-300x fewer tokens than a plain Read/Grep workflow on the everyday tasks (orientation, outlining a large file, a symbol's callers), measured across 7 real, unmodified open-source repos on dekko 0.43.77. The floor, a small grep-friendly local symbol, is about 2.5x. The full breakdown is right below.

Why dekko?

Most agent workflows gather context by reading whole files or grepping across a repo — expensive, and it throws away structure (who calls what, what a function's fan-in/fan-out looks like). dekko instead parses the repo once into a call graph and answers targeted questions against it. Measured across 7 real, unmodified open-source repos (Go, TypeScript, Java, Rust, Python/C++ — up to 14k files, 172k symbols) on dekko 0.43.77, dekko's structured queries used 10x–300x fewer tokens than the equivalent Read/Grep workflow for the same task (repo orientation, outlining a large file, tracing a symbol's callers).

TaskExample repo (scale)dekkoRead/GrepSavings
Repo orientation (summary)awesome-go (10 files)359 tok~16,328 tok~45x
Repo orientation (summary)claude-buddy (57 files)~349 tok~113,514 tok (every source file)~325x
Outline a large fileclaude-code REPL.tsx (5,005 lines)~1,154 tok~223,963 tok~194x
Outline a large filecline SdkController.ts (84 KB)1,803 tok~21,023 tok~11.7x
Outline a directoryzed crates/git_ui/src (32 files)~35,778 tok~418,520 tok~11.7x
Callers of a symbolclaude-code errorMessage~602 tok~18,521 tok (323+ grep hits)~31x
Callers of a symbolzed MultiWorkspace.new (22 sites, 8 files)~809 tok~381,446 tok (read the caller files)~471x
External-API usageclaude-code chalk~798 tok~8,099 tok~10x
Bundled context (workset)awesome-go ToHTML263 tok4,104 tok~16x

dekko's cost stays roughly flat per query while Read/Grep scales with file/repo size, so the ratio grows with scale. It's fast in wall-clock terms too: mapping dekko's own ~4,300-symbol codebase from a cold cache takes about 5 seconds on all cores, an incremental remap after an edit is well under a second, and queries against the resulting map return instantly. The win isn't universal — small, self-contained files and already-grep-friendly local symbols see little benefit (the floor measured was about 2.5x). See benchmarks/real-world-repos/ for the full per-task breakdown, methodology, the original 2026-08 study, and the correctness caveats it raised and how they were closed.

Compared to tag-index tools like ctags/gtags, dekko resolves actual call edges (not just definitions), ranks files by load-bearing-ness, and speaks directly to agents over MCP or the CLI — no editor plugin required.

Install

sh
uv tool install dekko      # or: pip install dekko / pipx install dekkodekko --claude-install     # add the /map command + MCP server to Claude Code, then restart

Extras (dekko[all] for 43 more languages, dekko[search] for embedding search), installing from a local clone, and uninstalling are in docs/install.md.

Quick start

sh
cd my-projectdekko map                  # writes .dekko/MAP.md + .dekko/map.jsondekko summary               # ~40-line digest: dirs, hotspots, entry points

.dekko/ is git-ignored by default; the map regenerates on demand, so you rarely need to run dekko map again by hand. If your repo has languages outside the default Tier-1 set (Python, C, C++, JS/TS, Go, Java, Kotlin, Rust), dekko map will say so per file; install dekko[all] for 43 more languages (see Install) and re-run. The list says how well each one is read.

Documentation

  • docs/install.md — installation, extras, local clone, uninstall
  • docs/cli.md — every CLI command, symbol targets, excluding files, notes, daemon mode, language support
  • docs/claude-code.md — the /map plugin, push hooks, Claude Code skills, the MCP server, and Cline

Learn more

  • CHANGELOG.md — per-version history
  • CONTRIBUTING.md — dev setup, testing, releasing
  • benchmarks/ — token-efficiency measurements, including a 7-repo real-world comparison against a plain Read/Grep workflow

來源:README.md,提交 6d46175

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

11
  1. v1.9.0最新Oct 9, 2026
  2. v1.8.0Oct 7, 2026
  3. v1.7.0Oct 6, 2026
  4. v1.6.0Oct 2, 2026
  5. v1.5.0Sep 27, 2026
  6. v1.3.0Sep 26, 2026
  7. v1.2.0Sep 25, 2026
  8. v1.1.0Sep 24, 2026
  9. v1.0.0Sep 22, 2026
  10. v0.43.71Sep 22, 2026
  11. v0.43.49Sep 16, 2026

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