gwt-project-index — community gwt-project-index, community, ide skills, Claude Code, Cursor, Windsurf

v1.0.0

このスキルについて

ChromaDB embeddings を使用した効率的なプロジェクトファイルおよび GitHub Issue 検索機能が必要な AI エージェントに最適です。 Distributed LLM router with load balancing and automatic model distribution

akiojin akiojin
[2]
[0]
Updated: 3/12/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 7/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution
Review Score
7/11
Quality Score
49
Canonical Locale
ja
Detected Body Locale
ja

ChromaDB embeddings を使用した効率的なプロジェクトファイルおよび GitHub Issue 検索機能が必要な AI エージェントに最適です。 Distributed LLM router with load balancing and automatic model distribution

このスキルを使用する理由

分散型 LLM ルーター、負荷分散、自動モデル配布を使用して、ChromaDB embeddings を活用した効率的なプロジェクトファイルおよび GitHub Issue 検索を実現し、GitHub Issues 検索などのプロトコルをサポートします。

おすすめ

ChromaDB embeddings を使用した効率的なプロジェクトファイルおよび GitHub Issue 検索機能が必要な AI エージェントに最適です。

実現可能なユースケース for gwt-project-index

手動検索前に、仕様の統合のために GitHub Issues を検索します
プロジェクトファイルおよび GitHub Issues のベクトル検索インデックスを維持します
開発ワークフローの効率化のために、プロジェクト構造のインデックスを自動化します

! セキュリティと制限

  • ChromaDB embeddings が必要です
  • GitHub Issues 検索に依存しています
  • GitHub Issue 統合を持つプロジェクトのみに限定されています

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

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Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is gwt-project-index?

ChromaDB embeddings を使用した効率的なプロジェクトファイルおよび GitHub Issue 検索機能が必要な AI エージェントに最適です。 Distributed LLM router with load balancing and automatic model distribution

How do I install gwt-project-index?

Run the command: npx killer-skills add akiojin/llmlb/gwt-project-index. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for gwt-project-index?

Key use cases include: 手動検索前に、仕様の統合のために GitHub Issues を検索します, プロジェクトファイルおよび GitHub Issues のベクトル検索インデックスを維持します, 開発ワークフローの効率化のために、プロジェクト構造のインデックスを自動化します.

Which IDEs are compatible with gwt-project-index?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for gwt-project-index?

ChromaDB embeddings が必要です. GitHub Issues 検索に依存しています. GitHub Issue 統合を持つプロジェクトのみに限定されています.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add akiojin/llmlb/gwt-project-index. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use gwt-project-index immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

gwt-project-index

Install gwt-project-index, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Project Structure Index

gwt maintains a vector search index of all project files and GitHub Issues using ChromaDB embeddings.

Issues search first for spec integration

When the user asks any of the following, use GitHub Issues search before manual gh issue list, title grep, or file search:

  • "既存仕様を探して"
  • "どの SPEC に統合するべきか"
  • "関連 Issue / spec を探して"
  • "Project Index の統合仕様を確認して"
  • "bug / feature の過去設計を見たい"

For spec integration work, the first question is not "which file should I edit?" but "which existing gwt-spec Issue is the canonical destination?".

Minimum workflow:

  1. Update the Issues index with index-issues
  2. Run search-issues with 2-3 semantic queries derived from the request
  3. Pick the canonical existing spec if found
  4. Only fall back to creating a new spec when no suitable canonical spec exists

Suggested query patterns:

  • subsystem + purpose
    • project index issue search spec
  • user-facing problem + architecture term
    • chroma persisted db recovery project index
  • workflow / discoverability requirement
    • LLM should use gwt-project-index before spec creation

File search command

Run in terminal to find files related to a feature or concept:

bash
1~/.gwt/runtime/chroma-venv/bin/python3 ~/.gwt/runtime/chroma_index_runner.py \ 2 --action search \ 3 --db-path "$GWT_PROJECT_ROOT/.gwt/index" \ 4 --query "your search query" \ 5 --n-results 10

On Windows, use ~/.gwt/runtime/chroma-venv/Scripts/python.exe as the Python executable.

File search output format

JSON object with ranked results:

json
1{"ok": true, "results": [ 2 {"path": "src/git/issue.rs", "description": "GitHub Issue commands", "distance": 0.12}, 3 {"path": "src/lib/components/IssuePanel.svelte", "description": "Issue list panel", "distance": 0.25} 4]}

GitHub Issues search command

First, update the Issues index (fetches gwt-spec Issues via gh CLI):

bash
1~/.gwt/runtime/chroma-venv/bin/python3 ~/.gwt/runtime/chroma_index_runner.py \ 2 --action index-issues \ 3 --db-path "$GWT_PROJECT_ROOT/.gwt/index"

Then search Issues semantically:

bash
1~/.gwt/runtime/chroma-venv/bin/python3 ~/.gwt/runtime/chroma_index_runner.py \ 2 --action search-issues \ 3 --db-path "$GWT_PROJECT_ROOT/.gwt/index" \ 4 --query "your search query" \ 5 --n-results 10

Issues search output format

json
1{"ok": true, "issueResults": [ 2 {"number": 42, "title": "Add vector search for Issues", "url": "https://github.com/...", "state": "open", "labels": ["gwt-spec"], "distance": 0.08} 3]}

When to use

  • Spec integration: find the canonical gwt-spec Issue before creating or updating a spec
  • Task start: search for files and Issues related to the assigned feature
  • Bug investigation: find files and spec Issues that might relate to the bug
  • Feature addition: locate existing similar implementations and relevant specs
  • Architecture understanding: discover how components are organized

Environment

  • GWT_PROJECT_ROOT: absolute path to the project root (set by gwt at pane launch)

Notes

  • File index is auto-generated when the project is opened in gwt
  • Issue index must be updated manually (via GUI "Update Index" button or index-issues action)
  • Both use semantic similarity (not just keyword matching)
  • Lower distance values indicate higher relevance
  • For spec work, prefer search-issues first and use file search second

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