Lousy AgentsBLOCK
Bootstrap projects with pre-configured instructions, tests, and linters that guide AI coding agents to produce reliable code
Overview
From the repository's own README, as read at the audited commit. Badges and raw HTML are left out.
[](https://scorecard.dev/viewer/?uri=github.com/zpratt/lousy-agents)
Turn "lousy" AI outputs into production-grade code.
TL;DR
Lousy Agents is a set of published npm packages for agentic software development, with @lousy-agents/cli as the main entry point. Run npx @lousy-agents/cli init to create a new project with testing, linting, and GitHub Copilot configuration. Run npx @lousy-agents/cli copilot-setup in existing projects to generate a workflow that gives Copilot your environment context. Add @lousy-agents/mcp for MCP integrations and @lousy-agents/agent-shell for npm script telemetry when you need them.
Lousy Agents is an npm workspace monorepo that publishes focused packages for scaffolding, MCP integrations, and npm script telemetry. The CLI package gives you a production-ready development environment with testing, linting, and AI assistant configuration in one command.
Quick Start
# Scaffold a new webapp project (no install required) npx @lousy-agents/cli init --kind webapp # Or use interactive mode to choose your project type npx @lousy-agents/cli init # Generate GitHub Copilot setup workflow from your project configuration npx @lousy-agents/cli copilot-setup
Table of Contents
- Start Here
- Who This Is For
- Why This Exists
- Features
- Installation
- Usage
- Contributing
- Roadmap
- Documentation
- Reference Examples
Start Here
If you're adopting Lousy Agents for the first time, use this order:
- Scaffold a project with
npx @lousy-agents/cli init - Add repository-specific setup with
npx @lousy-agents/cli copilot-setup - Add deeper integrations only if you need them:
- `@lousy-agents/mc
816e4c351244OBSERVED · 2026-10-12Connect
Built from this server's own package name, version and transport as found in its source — not copied from anyone's documentation, so it cannot drift against a page we do not control. Replace the environment placeholders with a token scoped to the least it needs.
claude mcp add mcp --env GH_TOKEN=${GH_TOKEN} --env GITHUB_TOKEN=${GITHUB_TOKEN} -- npx -y @lousy-agents/[email protected]{
"mcpServers": {
"mcp": {
"command": "npx",
"args": [
"-y",
"@lousy-agents/[email protected]"
],
"env": {
"GH_TOKEN": "${GH_TOKEN}",
"GITHUB_TOKEN": "${GITHUB_TOKEN}"
}
}
}
}Exposed tools (22)
16 read · 6 write · 0 destructive.
| Tool | Risk | Description |
|---|---|---|
analyze_action_versions | read | Analyze GitHub Action versions used across all workflow files in a target directory |
analyze_instruction_quality | read | Analyze the structural quality of feedback loop documentation in instruction files. Assesses structural context, execution clarity, and loop completeness across all supported instruction formats. |
capture | write | Generate a lesson capture prompt for Stop/SubagentStop Claude hooks |
context | read | Inject relevant lessons into Claude hooks as additionalContext |
copilot-setup | write | Generate or update the Copilot Setup Steps workflow based on detected environment configuration |
create_claude_code_web_setup | write | Create or update Claude Code web environment setup (.claude/settings.json with SessionStart hooks and CLAUDE.md documentation) based on detected environment configuration. |
create_copilot_setup_workflow | write | Create or update the Copilot Setup Steps workflow (copilot-setup-steps.yml) based on detected environment configuration. Returns actions needing version resolution and instructions for SHA-pinning. |
discover_environment | read | Discover environment configuration files (mise.toml, version files like .nvmrc, .python-version, etc.) in a target directory |
discover_feedback_loops | read | Discover npm scripts from package.json and CLI tools from GitHub Actions workflows, mapping them to SDLC feedback loop phases (test, build, lint, format, security, etc.) |
discover_workflow_setup_actions | read | Discover setup actions used in existing GitHub Actions workflows in a target directory |
doctor | read | Diagnose agentic configuration across harnesses: inventory, classify, and evaluate preconditions |
init | read | Initialize a new project with lousy agents scaffolding |
init-hooks | read | Initialize Claude Code hook configuration for lousy-agents context injection |
lessons | read | Validate lesson files in .lousy-agents/lessons/ against the lesson schema |
lint | read | Lint agent skills, custom agents, instruction files, and hook configurations. Validates frontmatter, instruction quality, and hook config schemas. Also supports flag-only (not default-on) subagent and MCP server config linting. Run |
new | write | Create new resources (e.g., Copilot agents, skills). Use |
read_copilot_setup_workflow | read | Read the existing Copilot Setup Steps workflow (copilot-setup-steps.yml or .yaml) from a target directory |
resolve_action_versions | read | Get version resolution metadata for GitHub Actions. Returns lookup URLs and instructions for the LLM to fetch latest versions and SHA-pin them. Can be called independently of workflow creation. |
reviewer | read | A reviewer subagent |
security | read | A security agent |
skill | write | Create a new GitHub Copilot Agent Skill. Example: lousy-agents new skill github-actions-debug |
validate_instruction_coverage | read | Validate that repository instructions (.github/copilot-instructions.md and .github/instructions/*.md) document all mandatory feedback loop scripts and tools. Returns coverage percentage and suggestions for missing documentation. |
Trust audit
BLOCKgrade F · trust 53/100 Do not install this without reading the findings. The audit found something that could harm you or your machine.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | WARN |
| L1 | Static analysis of the code | FAIL |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- declared (5 observation(s))
- Shell
- declared (8 observation(s))
- Dependencies
- not all pinned
- Secrets in source
- none-found
Findings (25)
exec(cmd);
- pattern: exec($CMD,...)
injection risk applies to exec('git clone ' + url),.claude/skills/curate-release
.claude/skills/feature-to-plan
.claude/skills/mutation-hunter
.claude/skills/plan-to-graph
.claude/skills/rugged-evil-tester
baseUrl = `http://127.0.0.1:${address.port}`;.dependency-cruiser.cjs
.dependency-cruiser.webpack.cjs
.gitmodules
.graphifyignore
.graphifyinclude
validateDirectory("foo/../../bar"),const result = resolveSafePath(repoRoot, "../../etc/passwd");
"src/../../../../../../etc/shadow",
const result = resolveSafePath("/", "../../etc/passwd");const result = resolveSafePath("/", "../../../");{ name: "test|tee /tmp/exfil", command: "vitest run" },expect(policy.allow).not.toContain("mise run test|tee /tmp/exfil");it("should reject to prevent symlink-based file exfiltration", async () => {@lousy-agents/agentic-doctor, @lousy-agents/core, @lousy-agents/lint
@lousy-agents/core
@lousy-agents/core
Gates applied: no_behavioural_pass.
816e4c351244full audit observations/trust-audit/mcp-server/zpratt__lousy-agents.json · Report an issue / request a re-scanAudit history
Every audit this server has had. A grade with a past is a grade somebody is still checking.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-12 | 816e4c351244 | BLOCK | F | 53 | first audit |
Questions
What is the @lousy-agents/mcp MCP server?
Bootstrap projects with pre-configured instructions, tests, and linters that guide AI coding agents to produce reliable code
What tools does @lousy-agents/mcp expose?
22 in total: 16 read-only, 6 that write, and 0 that can delete or overwrite. Every one is listed on this page with its risk.
Is @lousy-agents/mcp safe to connect to an agent?
No — not without reading the findings first. The audit graded it F (53/100) and found 3 critical or high issues in the source. Each one is listed on this page with the file and line it is on.
What credentials does @lousy-agents/mcp need?
It reads GH_TOKEN and GITHUB_TOKEN from the environment. Give it a token scoped to the least it needs — an agent that can be talked into calling a tool can be talked into calling it with your credentials.
How does @lousy-agents/mcp run?
It speaks stdio, so it runs as a local process your client starts. It is published on npm as @lousy-agents/mcp at 1.0.2.
How current is this page?
The grade is for one exact copy of the source (816e4c351244), read on 2026-10-12. The repository is watched and re-audited when it changes.