ai-agent-guidelines
A Model Context Protocol (MCP) server offering professional tools and templates for hierarchical prompting, code hygiene, visualization, memory optimization, and agile planning.
Installation
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Documentation
mcp-ai-agent-guidelines
[!CAUTION] Experimental / Early Stage: This research demonstrator project references thirdβparty models, tools, pricing, and docs that evolve quickly. Treat outputs as recommendations and verify against official docs and your own benchmarks before production use.
A TypeScript ESM MCP server exposing 20 public instruction tools and 7 utility tools, backed by 102 internal skills across 18 domain families β from requirements discovery and code quality through governance, resilience, and physics-inspired analysis.
π Full documentation on GitHub Pages
Table of Contents
- Requirements
- Installation
- VS Code Integration (One-Click)
- MCP Server Configuration
- CLI Usage
- Features
- Instruction Workflows
- Skill Taxonomy
- Configuration
- Development
- Environment Variables
- Contributing
- License
Requirements
| Runtime | Version |
|---|---|
| Node.js | β₯ 22.7.5 |
| npm | β₯ 10.0.0 |
Installation
npx (zero-install, recommended for MCP config)
npx -y mcp-ai-agent-guidelines@latest
Global install
npm install -g mcp-ai-agent-guidelines
# MCP stdio server entrypoint
mcp-ai-agent-guidelines
# Interactive CLI
mcp-cli info
Local install (monorepo / project dependency)
npm install mcp-ai-agent-guidelines
VS Code Integration (One-Click)
Click a badge below to add this MCP server directly to VS Code (User Settings β mcp.servers):
Or add manually to User Settings JSON:
{
"mcp": {
"servers": {
"ai-agent-guidelines": {
"command": "npx",
"args": ["-y", "mcp-ai-agent-guidelines@latest"]
}
}
}
}
Using Docker:
{
"mcp": {
"servers": {
"ai-agent-guidelines": {
"command": "docker",
"args": ["run", "--rm", "-i", "ghcr.io/anselmoo/mcp-ai-agent-guidelines:latest"]
}
}
}
}
MCP Server Configuration
Add the server to your MCP host config. The entry-point is dist/index.js and communicates over stdin/stdout.
Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json)
[!IMPORTANT] Claude Desktop spawns the server with a different working directory than your project. Set
MCP_WORKSPACE_ROOTto the absolute path of the project you want the server to write state into.
{
"mcpServers": {
"ai-agent-guidelines": {
"command": "npx",
"args": ["-y", "mcp-ai-agent-guidelines@latest"],
"env": {
"MCP_WORKSPACE_ROOT": "/absolute/path/to/your/project"
}
}
}
}
VS Code (.vscode/mcp.json or user settings)
{
"servers": {
"ai-agent-guidelines": {
"type": "stdio",
"command": "npx",
"args": ["-y", "mcp-ai-agent-guidelines@latest"],
"env": {
"MCP_WORKSPACE_ROOT": "${workspaceFolder}"
}
}
}
}
From local build
{
"mcpServers": {
"ai-agent-guidelines": {
"command": "node",
"args": ["/path/to/repo/dist/index.js"]
}
}
}
CLI Usage
An interactive CLI wizard is included for standalone use outside an MCP host. The published package exposes two entrypoints:
mcp-ai-agent-guidelinesβ MCP stdio server entrypoint for editors and MCP hostsmcp-cliβ interactive CLI for onboarding, orchestration, and diagnostics
# Project onboarding
mcp-cli onboard init
# Re-open the orchestration editor
mcp-cli orchestration edit
# Quick re-entry for environment + model fleet only
mcp-cli orchestration edit --quick
# Direct skill invocation
mcp-cli --skill core-prompt-engineering --request "Write a system prompt for a coding assistant"
Instruction-tool input schema β the public instruction workflows share this shape:
{
request: string; // required β the task description
context?: string; // optional β background context
options?: object; // optional β skill-specific overrides
}
Configuration Files
.mcp-ai-agent-guidelines/config/orchestration.tomlβ primary orchestration authority (local, not tracked in git)src/config/orchestration-defaults.tsβ builtin bootstrap defaults used to auto-create the workspace config in advisory mode whenorchestration.tomlis absent
First-time runs auto-create orchestration.toml from builtin advisory defaults, including semantic role placeholders so routing can proceed before model discovery. Run mcp-cli onboard init to customize the setup or mcp-cli orchestration edit to reopen the interactive editor.
Features
- 20 public instruction tools exposed through the MCP instruction surface
- 7 public utility tools for workspace, memory, session, snapshot, orchestration, model-discovery, and visualization operations (before any
HIDDEN_TOOLSfiltering) - 102 internal skills across 18 domain prefixes β see Skill Taxonomy
- Physics-inspired analysis: 15 quantum-mechanics (
qm-*) + 15 general-relativity (gr-*) skills - Bio-inspired adaptive routing: ACO, Hebbian, Slime-mould, Quorum, Homeostatic, Clone-Mutate, Replay
- Governance layer: prompt-injection hardening, PII guardrails, policy validation, regulated-workflow design
- Model orchestration guidance: 5 multi-model patterns (parallel critique, draft-review, majority vote, cascade, free triple)
- Zero runtime LLM calls β advisory outputs; wire a concrete executor to enable real LLM dispatch
- xstate v5 state-machine orchestration built-in
- graphology graph routing for topological skill sequencing
Public MCP Surface
ListTools currently exposes 27 tools total:
| Category | Count | Tools |
|---|---|---|
| Instruction (workflow) | 17 | meta-routing, bootstrap, implement, refactor, debug, testing, design, review, research, orchestrate, adapt, resilience, evaluate, prompt-engineering, plan, document, govern |
| Instruction (discovery) | 3 | enterprise, physics-analysis, onboard_project |
| Utility | 7 | agent-workspace, agent-memory, agent-session, agent-snapshot, orchestration-config, model-discover, graph-visualize |
The 102 skill definitions are internal workflow assets β not individually exposed as MCP tools. See docs for full tool reference.
Skill Taxonomy
Skills are organised under 18 domain-specific prefixes:
| Prefix | Domain | Count |
|---|---|---|
req- | Requirements Discovery | 4 |
orch- | Orchestration | 4 |
doc- | Documentation | 4 |
qual- | Code Analysis & Quality | 5 |
synth- | Research & Synthesis | 4 |
flow- | Workflow | 3 |
eval- | Evaluation & Benchmarking | 5 |
debug- | Debugging | 4 |
strat- | Strategy & Decision Making | 4 |
arch- | Architecture Design | 4 |
prompt- | Prompting | 4 |
adapt- | Bio-inspired Adaptive Routing | 5 |
bench- | Advanced Evals | 3 |
lead- | Leadership & Enterprise | 7 |
resil- | Resilience & Self-repair | 5 |
gov- | Safety & Governance | 7 |
qm- | Quantum Mechanics metaphors | 15 |
gr- | General Relativity metaphors | 15 |
Physics skills (
qm-*,gr-*) require explicit justification before invocation. Route through thephysics-analysisinstruction first.
Full taxonomy details: docs/architecture/03-skill-graph.md.
Instruction Workflows
20 mission-driven instruction workflows orchestrate internal skills into complete task flows:
| Instruction | Purpose |
|---|---|
meta-routing | Master routing β choose which instruction to invoke |
bootstrap | Scope clarification and requirements extraction |
implement | Build new features end-to-end |
refactor | Improve existing code safely |
debug | Diagnose and fix problems |
testing | Write, run, and verify tests |
design | Architecture and system design |
review | Code quality and security review |
research | Synthesis, comparison, recommendations |
orchestrate | Compose multi-agent workflows |
adapt | Bio-inspired adaptive routing |
resilience | Self-healing and fault tolerance |
evaluate | Benchmark and assess AI quality |
prompt-engineering | Build, evaluate, optimise prompts |
plan | Strategy, roadmap, sprint planning |
document | Generate documentation artifacts |
govern | Safety, compliance, guardrails |
enterprise | Leadership and enterprise-scale AI strategy |
physics-analysis | QM + GR physics-inspired codebase analysis |
onboard_project | Session-start project orientation |
Architecture
See docs/architecture/ for ADRs and full module layout. The entry-point is src/index.ts; instructions live in src/instructions/, skills in src/skills/, and generated tool definitions in src/generated/ (do not edit by hand).
Development
# Install dependencies
npm install
# Type-check
npm run type-check
# Build (tsc β dist/)
npm run build
# Watch mode
npm run dev
# Run MCP server
node dist/index.js
Code Quality
npm run check # biome check (lint + format)
npm run check:fix # auto-fix
npm run quality # full suite: verify_matrix + type-check + workflow-docs + biome
Regenerate generated tool definitions after editing canonical registries or workflow specs
python3 scripts/generate-tool-definitions.py
npm run build
Verify skill/instruction coverage matrix (zero orphans required)
python3 scripts/verify_matrix.py
Testing
npm test # vitest run
npm run test:coverage # vitest + v8 coverage (80% threshold)
Tests live both co-located with source (src/**/*.test.ts) and in src/tests/.
Published package note: the npm package ships dist/, README.md, and LICENSE. Repository-only source assets such as docs/, .github/, and scripts/ are development references, not package runtime files.
Environment Variables
| Variable | Default | Description |
|---|---|---|
HIDDEN_TOOLS | "" | Comma-separated list of tool names to exclude from ListTools |
LOG_LEVEL | "info" | Observability log level (debug, info, warn, error) |
ALLOW_GOVERNANCE_SKILLS | unset / "false" | Must be true to allow gov-* skills through criticalSkillGuard |
DISABLE_ADAPTIVE_ROUTING | unset / "false" | Set to true to hide routing-adapt and block adapt-* skills; enabled by default (opt-out model) |
ALLOW_INTENSIVE_SKILLS | unset / "false" | Must be true to allow resource-intensive skills such as bench-eval-suite, eval-prompt-bench, qm-path-integral-historian, and gr-spacetime-debt-metric |
ENABLE_PHYSICS_SKILLS | unset / "false" | Required by input validation when physics skills are not otherwise authorized; physics skills also require conventional-evidence schema validation |
MCP_WORKSPACE_ROOT | unset | Absolute path to the project directory the server should write state into (.mcp-ai-agent-guidelines/). Required when using npx via Claude Desktop, Cursor, or Windsurf β these clients do not preserve the terminal's working directory. VS Code supports ${workspaceFolder}. |
MCP_SLIM_MODE | unset / "false" | Set to true to expose only the minimal surface: task-bootstrap, meta-routing, and project-onboard (useful for low-context agents) |
Skill gates
Skill execution is gated by environment variables above. Physics skills (qm-*, gr-*) additionally require ENABLE_PHYSICS_SKILLS=true and conventional-evidence input. Model availability is derived from .mcp-ai-agent-guidelines/config/orchestration.toml; strict_mode = false allows warnings-only, strict_mode = true blocks on missing models.
Auto Mode & Session Hooks
Long-running agent sessions (VS Code Copilot, Claude Code, Copilot CLI) can drift away from MCP tools after the first few exchanges. The session hooks mechanism counteracts this by injecting lightweight reminders at the IDE lifecycle boundaries.
What the hooks do
| Hook | Trigger | Effect |
|---|---|---|
SessionStart | New chat session begins | Reminds agent to call task-bootstrap / meta-routing first |
PreToolUse | Before every tool call | Detects consecutive non-MCP calls; nudges agent to re-orient |
Quick install
# VS Code / Copilot CLI (writes to ~/.copilot/hooks/)
mcp-cli hooks setup --client vscode
# Claude Code (writes to ~/.claude/)
mcp-cli hooks setup --client claude-code
# Inspect what will be written without touching the filesystem
mcp-cli hooks print --client vscode
Manual install
Copy the following JSON to ~/.copilot/hooks/mcp-ai-agent-guidelines-hooks.json:
{
"hooks": {
"SessionStart": [
{
"type": "command",
"command": "mcp-ai-agent-guidelines hooks remind-session"
}
],
"PreToolUse": [
{
"type": "command",
"command": "mcp-ai-agent-guidelines hooks remind-drift"
}
]
}
}
Routing guidance
The .agent/rules/ directory contains IDE-readable routing tables:
.agent/rules/default.mdβ universal symptom β tool pipeline table and anti-patterns.agent/rules/copilot.mdβ VS Code Copilot-specific quick reference and session-start checklist
These files are automatically picked up by Copilot's custom instructions system and by Serena's hook integration layer.
[!NOTE] The published npm package does not include
.agent/rules/. If you install from npm and want these routing rules, copy them from the GitHub repository into your workspace.
Contributing
Contributions welcome! See CONTRIBUTING.md for guidelines, code standards, and the skill/instruction development workflow.
License
MIT Β© 2025 Anselmoo
