How to Install gstack Framework and Configure It for AI Coding Agents

Overview

How It Works

Step-by-Step

1. Step 1: Identify Your Agent's Command Directory

   Before cloning anything, determine where your AI coding agent expects custom command files to live. claude/commands/ inside your project root. cursor/rules/. For other agents, check the documentation for custom instruction or system prompt file locations.

   If you are unsure, create a test file in the candidate directory, add a simple instruction like "respond with HELLO", and see if the agent picks it up when you invoke the corresponding command. Document the exact path because you will need it in the next step. Also note whether the agent supports subdirectories within the command folder, since gstack organizes skills into categories using subdirectories.

   Tip: If you are using multiple agents on the same project, you can symlink gstack's files into each agent's command directory rather than duplicating them. This keeps a single source of truth.

2. Step 2: Clone the gstack Repository

   Open your terminal and navigate to your project root. gstack-source (or whatever the current repo URL is). gstack-source rather than directly into the commands folder gives you a clean copy you can update with git pull later without worrying about merge conflicts with any local customizations. Verify the clone completed by listing the contents.

   You should see directories for skills, power tools, and a project context template. If the repo structure has changed since this guide was written, read the repo's own README for the current layout.

   Tip: Add `.gstack-source/` to your project's `.gitignore` if you do not want the raw gstack source tracked in your project repo. Alternatively, add it as a git submodule if you want versioned updates.

3. Step 3: Copy or Symlink Command Files into the Agent Directory

   Copy the skill and power tool markdown files from your staging directory into the agent's command directory. claude/commands/. You have two options: a flat copy where all files go into one directory, or a structured copy that preserves gstack's subdirectory organization. The structured approach is better because it keeps skills grouped by category and makes the /help` index more readable.

   md`). After copying, count the files. You should have 23 specialist skill files and 8 power tool files, plus any index or help files. If the count is wrong, check for hidden files or a partial clone.

   Tip: Using symbolic links instead of copies means updates to the source directory propagate automatically. On macOS and Linux, use `ln -s ../../../.gstack-source/skills/ .claude/commands/skills`. On Windows, use `mklink /D`.

4. Step 4: Create and Configure the Project Context File

   The project context file is what transforms gstack from a generic skill pack into a project-specific one. md`) into your project root or the location gstack's skills expect to find it. Open the template and fill in every section: project name, tech stack, architecture overview, directory structure, coding conventions, testing strategy, deployment pipeline, and any constraints or non-negotiables. Be specific.

   " The more detail you provide, the more grounded the agent's output will be. Save the file and note its path, because you may need to update references in the skill files.

   Tip: If you already have an architecture decision record (ADR) or a CONTRIBUTING.md, reference or inline the relevant sections rather than writing from scratch. Existing documentation is more accurate than memory.

5. Step 5: Update Path References in Skill Files

   Some gstack skill files contain relative paths that reference the project context file or other skills. md`). If the paths do not resolve correctly given your directory structure, update them. The most common issue is that the skill file assumes a specific nesting depth that does not match your layout.

   md`. Test one path by asking the agent to read the context file from within a skill invocation. If the agent says it cannot find the file, the path is wrong.

   Tip: Consider using a simple find-and-replace script to update all path references at once. Something like `find .claude/commands -name '*.md' -exec sed -i 's|old/path|new/path|g' {} +` saves time and prevents inconsistencies.

6. Step 6: Verify Command Resolution

   This is the most important step and the one most people skip. Open your AI coding agent in your project directory and try invoking three commands from different categories: one specialist skill (like /dev or /qa), one power tool (like /think or /plan), and the help or index command. For each one, check three things. First, does the command resolve at all, or does the agent respond with a generic answer?

   Second, does the agent's behavior match the skill definition, meaning does it ask the right questions, follow the right structure, and adopt the right role? Third, does the agent reference your project context, mentioning your tech stack, conventions, or architecture? If any of these checks fail, you have a configuration issue. A command that resolves but ignores context is usually a path reference problem.

   A command that does not resolve at all is a file placement problem.

   Tip: Create a simple checklist of all 23 skills and 8 power tools and check them off as you verify each one. It takes 10 minutes and catches issues that surface only with specific commands.

7. Step 7: Configure Multi-Agent Perspectives

   gstack uses multi-agent perspectives (CEO, engineer, QA, and others) to structure development conversations. These perspectives are defined in configuration within the skill files or a separate perspectives file. Review the default perspective definitions and customize them for your team's actual roles and concerns. For example, if your organization has strict compliance requirements, you might add a compliance perspective or expand the QA perspective to include regulatory checks.

   If you are a solo developer, you might simplify the CEO perspective to focus on scope prioritization rather than organizational strategy. The perspectives should reflect real decision-making tensions in your project, not hypothetical ones. Save your changes and test by invoking a power tool that uses multiple perspectives, verifying that each perspective's voice is distinct and relevant to your project.

   Tip: Do not create more than 5 perspectives initially. Each perspective adds cognitive overhead to the agent's output. Start with the defaults, use them for a week, then add or modify based on what is actually missing from the conversations.

8. Step 8: Set Up Update and Maintenance Workflow

   gstack is an active open-source project, so new skills, refinements, and bug fixes will arrive over time. Decide now how you will handle updates. If you cloned into a staging directory, you can git pull to get the latest changes and then re-copy or re-sync the modified files into your commands directory. If you used symlinks, the update propagates automatically, but you should still check for new files that need linking.

   If you used a git submodule, run git submodule update --remote. Set a calendar reminder to check for updates monthly, or watch the repository for releases. When updating, always re-run the verification step from Step 6 to confirm nothing broke. Also check the changelog for any new skills or power tools that need to be added to your command directory.

   Tip: Pin gstack to a specific git tag or commit hash in production projects. Pull and test updates on a branch before merging into your main project. This prevents a gstack update from changing agent behavior mid-sprint.

Examples

Best Practices

• Commit gstack's command files (or symlinks) into your project repository so every team member and CI environment gets the same agent behavior. Keeping gstack in a personal dotfile directory means your teammates get vanilla agent responses while you get structured ones, which creates inconsistent code quality and confusing pull request reviews.

• Fill out the project context file completely before using any skills. A half-filled context file produces half-grounded agent output. The 15 minutes you spend writing a thorough context description saves hours of correcting agent suggestions that assume the wrong framework, testing strategy, or deployment target.

• Test command resolution in a fresh terminal session after installation, not in the same session where you were editing files. Some agents cache command lookups, and a stale cache can make a broken installation appear to work until you restart.

• Use the help or index command as your smoke test every time you update gstack or modify the directory structure. If the help command lists all 23 skills and 8 power tools with correct descriptions, your installation is healthy. If any are missing or show placeholder text, you have a file placement or path issue.

• Keep your customizations in separate files or clearly marked sections within gstack files, not intermixed with the original content. When you pull updates from the upstream repository, unmarked customizations get overwritten silently. A dedicated custom-overrides.md or clearly commented blocks make merges predictable.

• Version your project context file with the same discipline as your code. When your tech stack changes, your architecture evolves, or your conventions update, the context file must follow. Stale context is worse than no context because the agent will confidently produce output grounded in outdated assumptions.

• Start with the default configuration for your first week before customizing perspectives, disabling skills, or modifying workflows. The defaults encode opinionated but battle-tested patterns. Customizing before you understand the baseline means you might remove something valuable without knowing what you lost.

Common Mistakes

Frequently Asked Questions