---
title: "mattpocock/skills: Skills for Real Engineers"
section: "raw"
type: "source"
created: "2026-08-22"
updated: "2026-08-22"
canonical: "https://pyweb.dev/wiki/raw/articles/mattpocock-skills-repo-2026"
---
# mattpocock/skills: Skills for Real Engineers

**Author:** Matt Pocock  
**Repository:** https://github.com/mattpocock/skills  
**Description:** Modular skill system for coding agents (`.agents` / `.hermes` / `.claude`), codifying human software engineering discipline into machine-executable routines.

## Core Thesis & Philosophy
- **The AI Dilemma:** Approaches like GSD, BMAD, and Spec-Kit attempt to own the whole engineering process, removing developer control and making process bugs hard to diagnose.
- **Root Problem:** Bad code is the most expensive it has ever been. Autonomous agents generate high volume; without disciplined feedback loops, they create architectural "balls of mud", degrade the context window, and cause subsequent agent iterations to fail.
- **Fundamentals Matter More:** Good software engineering practices (small interfaces, deep modules, test-driven development, continuous domain modeling) are essential guardrails for AI agents.

## Skill Architecture & Invocation Models
Skills are split by invocation mechanics:
1. **User-Invoked Skills:** Interactive orchestration workflows explicitly triggered by the human (e.g. `/grill-me`, `/to-spec`, `/to-tickets`, `/implement`, `/wayfinder`, `/ask-matt`). They can invoke model-invoked skills, but never other user-invoked ones.
2. **Model-Invoked Skills:** Procedural and disciplined subroutines that can be triggered automatically by the agent or explicitly by the human (e.g. `/tdd`, `/diagnosing-bugs`, `/domain-modeling`, `/codebase-design`, `/code-review`, `/grilling`, `/writing-for-agents`).

## The Four Core Failure Modes & Skill Solutions
1. **The Agent Didn't Do What I Want:** Solved via relentless requirement sharpening (`/grill-me`, `/grill-with-docs`) before code is written.
2. **The Agent Is Too Verbose:** Solved via disciplined domain modeling (`/domain-modeling`, `CONTEXT.md`) so variable names, concepts, and interfaces are concise and unambiguous.
3. **The Code Doesn't Work:** Solved via automated feedback loops (`/tdd` with red-green-refactor, `/diagnosing-bugs` root-cause investigation).
4. **We Built A Ball Of Mud:** Solved via deep module architecture principles (John Ousterhout, *A Philosophy of Software Design*), pre-spec module quizzing (`/to-spec`), and proactive architectural audits (`/improve-codebase-architecture`).

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## Agent Navigation

### Machine endpoints
- Knowledge graph: https://pyweb.dev/api/graph.json
- Graph analysis: https://pyweb.dev/api/graph-analysis.json
- Context index: https://pyweb.dev/llms.txt