fundamental-principles

Enforces workspace-wide coding rules, verification workflows, and knowledge persistence for every task.

8|3|Updated Jun 8, 2019
One-click install
npx skills add https://github.com/e-picsa/picsa-apps --skill fundamental-principles-e-picsa
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fundamental-principles
Source: https://github.com/e-picsa/picsa-apps/tree/main/.agent/skills/fundamental-principles
Command: npx skills add https://github.com/e-picsa/picsa-apps --skill fundamental-principles-e-picsa

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? AI agents working in this repository often waste time on redundant builds, run destructive git commands, skip linting, or lose hard-won knowledge between sessions. This Skill establishes mandatory meta-instructions that govern every task, preventing costly mistakes and preserving learnings across sessions. ## Core Features & Use Cases - Auto-Knowledge Generation: Requires agents to check and append learnings to .agent/AI_GENERATED_KNOWLEDGE.md before and after complex tasks, building institutional memory. - Safe Verification Workflow: Mandates yarn ai:lint and yarn ai:test for changed-file-scoped linting and testing, while strictly prohibiting full builds and broad test suites. - Destructive Command Protection: Blocks git reset --hard, git clean -fd, rm -rf, and similar commands unless the user explicitly approves them. - PR Template Compliance: Enforces the .github/pull_request_template.md structure and preserves the PR-Agent AI summary block when creating pull requests. - Use Case: An agent fixing a bug in an Nx workspace automatically lints only changed files, runs colocated spec tests, records the root cause in the knowledge file, and drafts a compliant PR without touching uncommitted user work. ## Quick Start Apply the fundamental-principles rules to every task in this workspace, including scoped linting, knowledge logging, and PR template compliance.

Frequently Asked Questions about fundamental-principles

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I lint and test changed files in an Nx workspace?▼

Run yarn ai:lint with no arguments to auto-detect changed files versus HEAD and apply prettier plus eslint fixes, and run yarn ai:test to execute only the colocated spec files in the owning Nx project. Never run full builds or broad test suites.

What rules should an AI agent follow when working in a shared git repository?▼

An agent must never run destructive commands like git reset --hard, git clean -fd, or rm -rf without explicit user approval, since these can destroy uncommitted work. It should manually revert its own edits or ask permission first.

How can AI agents preserve knowledge between sessions?▼

Agents should check .agent/AI_GENERATED_KNOWLEDGE.md before starting complex tasks and append new entries after completing them. Entries document architectural patterns, bug root causes, and build or test workarounds for future sessions.

Does this workflow support Supabase database introspection?▼

Yes, the rules require using the supabase-db MCP query tool for schema exploration, function inspection, and table browsing. This is more accurate than grep-searching raw schema files.

When should a full application build be avoided during development?▼

Full builds with yarn build or yarn nx build should never run after code edits because they compile assets, run AOT passes, and bundle native wrappers, wasting time and tokens. Scoped linting and targeted tests provide sufficient verification.