Slash Command Manager
Integrates with Amazon Q AI assistant, generating slash commands installed to the Amazon Q prompts directory.
Integrates with Windsurf (built by Codeium), generating slash commands installed to the Windsurf global workflows directory.
Allows downloading prompts from public GitHub repositories to be used as slash commands.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Slash Command Managergenerate slash commands for Claude Code"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Slash Command Manager
A standalone CLI tool and MCP server for generating and managing slash commands as part of the Spec-Driven Development (SDD) workflow.
Overview
Slash Command Manager provides both a command-line interface (slash-man) for generating slash command definitions and an MCP server for programmatic access. This repository was extracted from the SDD Workflow repository to enable independent versioning and release cycles.
Related MCP server: @willpowell8/cursor-cloud-agent-mcp
Features
CLI Generator: Interactive command-line tool for creating slash command configurations
MCP Server: Programmatic API for generating slash commands via Model Context Protocol
Code Detection: Automatic detection of code patterns and generation of appropriate command structures
Flexible Configuration: Support for various configuration formats and customization options
Installation
Using uvx (Recommended)
Install and run directly from the repository:
# Generate slash commands for detected AI assistants
uvx --from git+https://github.com/liatrio-labs/slash-command-manager slash-man generate --yes
# View available commands
uvx --from git+https://github.com/liatrio-labs/slash-command-manager slash-man --helpOnce published to PyPI, you'll be able to use:
uvx slash-man generate --yesFrom Source
git clone https://github.com/liatrio-labs/slash-command-manager.git
cd slash-command-manager
uv pip install -e .Version Management
Slash Command Manager includes comprehensive version management with git commit SHA tracking:
Version Format
The version follows the format VERSION+COMMIT_SHA:
Development:
1.0.0+8b4e417(includes current git commit)Production:
1.0.0+def456(includes release commit at build time)Fallback:
1.0.0(when git commit unavailable)
Version Detection Priority
Build-time injection (for installed packages) - matches the release commit
Runtime git detection (for local development) - current git commit
Fallback - version only when git unavailable
Viewing Version
# Show version with git commit SHA
slash-man --version
slash-man -v
# Example output:
# slash-man 1.0.0+8b4e417This ensures traceability between installed versions and their corresponding git commits, useful for debugging and deployment tracking.
Quick Start
CLI Usage
# Generate slash commands for all detected AI assistants
slash-man generate
# Generate for specific agents (interactive selection)
slash-man generate --agents claude-code,cursor
# Generate with dry-run to preview changes
slash-man generate --dry-run
# View help
slash-man --help
# Clean up generated files
slash-man cleanupGitHub Repository Support
You can download prompts directly from public GitHub repositories using explicit flags:
# Download prompts from a GitHub repository directory
uv run slash-man generate \
--github-repo liatrio-labs/spec-driven-workflow \
--github-branch main \
--github-path prompts \
--agent claude-code \
--target-path /tmp/test-output
# Download from a branch with slashes in the name
uv run slash-man generate \
--github-repo liatrio-labs/spec-driven-workflow \
--github-branch refactor/improve-workflow \
--github-path prompts \
--agent claude-code \
--target-path /tmp/test-output
# Download a single prompt file from GitHub
uv run slash-man generate \
--github-repo liatrio-labs/spec-driven-workflow \
--github-branch refactor/improve-workflow \
--github-path prompts/generate-spec.md \
--agent claude-code \
--target-path /tmp/test-output
# Download from a nested path
uv run slash-man generate \
--github-repo owner/repo \
--github-branch main \
--github-path docs/prompts/commands \
--agent claude-code \
--target-path /tmp/test-outputImportant Notes:
All three GitHub flags (
--github-repo,--github-branch,--github-path) must be provided togetherGitHub flags are mutually exclusive with
--prompts-dir(cannot use both)Repository must be in format
owner/repo(e.g.,liatrio-labs/spec-driven-workflow)Only public repositories are supported
Only
.mdfiles are downloaded and processedThe
--github-pathcan point to either a directory or a single.mdfile
Error Handling:
# Invalid repository format
uv run slash-man generate --github-repo invalid-format --target-path /tmp/test-output
# Error: Repository must be in format owner/repo, got: 'invalid-format'. Example: liatrio-labs/spec-driven-workflow
# Missing required flags
uv run slash-man generate --github-repo owner/repo --target-path /tmp/test-output
# Error: All GitHub flags must be provided together. Missing: --github-branch, --github-path
# Mutual exclusivity error
uv run slash-man generate \
--prompts-dir ./prompts \
--github-repo owner/repo \
--github-branch main \
--github-path prompts \
--target-path /tmp/test-output
# Error: Cannot specify both --prompts-dir and GitHub repository flags simultaneouslyMCP Server Usage
Run the MCP server for programmatic access:
# STDIO transport (for MCP clients)
slash-man mcp
# HTTP transport
slash-man mcp --transport http --port 8000
# With custom configuration
slash-man mcp --config custom.toml --transport http --port 8080
# Or via uvx (once published)
uvx --from git+https://github.com/liatrio-labs/slash-command-manager slash-man mcpSupported AI Tools
The generator supports the following AI coding assistants:
Claude Code: Commands installed to
~/.claude/commandsCursor: Commands installed to
~/.cursor/commandsWindsurf: Commands installed to
~/.codeium/windsurf/global_workflowsCodex CLI: Commands installed to
~/.codex/promptsGemini CLI: Commands installed to
~/.gemini/commandsVS Code: Commands installed to platform-specific directories:
Linux:
~/.config/Code/User/promptsmacOS:
~/Library/Application Support/Code/User/promptsWindows:
%APPDATA%\Code\User\prompts
VS Code Insiders: Commands installed to platform-specific directories:
Linux:
~/.config/Code - Insiders/User/promptsmacOS:
~/Library/Application Support/Code - Insiders/User/promptsWindows:
%APPDATA%\Code - Insiders\User\prompts
OpenCode CLI: Commands installed to
~/.config/opencode/commandAmazon Q: Commands installed to
~/.aws/amazonq/prompts(Windows & macOS/Linux)Kiro CLI: Prompts installed to
~/.kiro/promptsInvoke with
@prompt-name(e.g.,@generate-spec)Note: Kiro CLI prompts do not support tool permissions. Run
/tools trust-allat the start of your session to auto-approve file operations (write, shell, etc.).
Kiro IDE: Steering files installed to
~/.kiro/steeringInvoke with
/prompt-nameslash command (e.g.,/generate-spec)Files have
inclusion: manualfrontmatter for manual inclusion
Documentation
Related Projects
SDD Workflow - Spec-Driven Development prompts and workflow documentation
Development
Testing in Clean Environment (Docker)
For testing the installation in a completely clean environment without any local dependencies, use these docker commands:
Option 1: One-line Testing
# Build and test in an ephemeral Docker container
docker run --rm -v $(pwd):/app -w /app python:3.12-slim bash -c "
pip install uv && \
uv sync && \
uv run slash-man generate --list-agents && \
echo '✅ Installation test passed - CLI is functional'
"This command:
Uses a fresh Python 3.12 slim container
Installs uv package manager
Syncs dependencies from scratch
Tests the CLI functionality
Automatically cleans up the container when done
For a more comprehensive test including package building:
# Full test: build package and test CLI in clean environment
docker run --rm -v $(pwd):/app -w /app python:3.12-slim bash -c "
pip install uv build && \
uv sync && \
python -m build && \
pip install dist/*.whl && \
slash-man generate --list-agents && \
slash-man generate --agent claude-code && \
ls -lh ~/.claude/commands/ | grep .md && \
echo '✅ Full installation and functionality test passed'
"Option 2: Interactive Docker Container
Build the Docker image and run it interactively:
# Build the Docker image
docker build -t slash-command-manager .
# Run interactively with shell access
docker run -it --rm slash-command-manager bash
# Or run directly with the CLI
docker run -it --rm slash-command-manager slash-man generate --list-agentsRunning Tests
# Run all tests
uv run pytest
# Run tests with coverage
uv run pytest --cov=mcp_server --cov=slash_commands --cov-report=term-missing
# Run pre-commit hooks
uv run pre-commit run --all-filesBuilding Package
# Build wheel and source distribution
uv run python -m build
# Install built package locally
pip install dist/*.whlSDD Workflow Integration
This package was extracted from the SDD Workflow repository to enable independent versioning and release cycles.
About SDD Workflow
The Spec-Driven Development (SDD) Workflow provides a structured approach to AI-assisted software development using three core prompts:
generate-spec: Creates detailed specifications from feature ideasgenerate-task-list-from-spec: Transforms specs into actionable task listsmanage-tasks: Coordinates execution and tracks progress
Slash Command Manager generates the slash commands that enable these prompts in your AI coding assistant. The workflow prompts themselves are maintained in the SDD Workflow repository.
Usage with SDD Workflow
Install Slash Command Manager (this package) to generate slash commands
Reference SDD Workflow prompts from the SDD Workflow repository when using the generated commands
For complete documentation on the SDD workflow, see the SDD Workflow repository.
License
Apache License 2.0 - see LICENSE file for details
Available Tools
1 toolbasic-exampleA
Return a static message for testing.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It indicates a read-like behavior ('return') but does not disclose details like whether the message is consistent across calls or any other constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using only six words. Every sentence is necessary, and it is front-loaded with the action and purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, output schema exists), the description completely covers what an agent needs to know to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, and schema coverage is 100%. Per guidelines, baseline is 4 for no parameters, and the description adds no extra param info, which is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a static message for testing, with a specific verb and resource. No siblings exist, so differentiation is not needed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for testing, providing clear context. No siblings or alternatives exist, so explicit when/when-not guidance is unnecessary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
v0.1.0- First observed
basic-example
TDQS
Only one tool exists, so there is no risk of confusion between tools. The single tool's purpose is clearly described.
With a single tool named 'basic-example', naming consistency is trivially maintained. The name uses a clear hyphenated pattern.
The server is titled 'Slash Command Manager' but provides only one test tool. This is far too few tools for the implied scope of managing slash commands.
The single tool is a static test example, offering no actual functionality for managing slash commands. The surface is severely incomplete relative to the server's purpose.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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