Agent skill

Code Quality Architecture

by jmfederico in jmfederico/pi-web

Project code quality and architecture expectations for implementation, refactoring, planning, and code review.

MITAuto-check passedDevelopment

Install Code Quality Architecture

skills CLI
$ npx skills add jmfederico/pi-web --skill code-quality-architecture -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jmfederico/pi-web code-quality-architecture --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jmfederico/pi-web.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/code-quality-architecture .claude/skills/code-quality-architecture && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
code-quality-architecture
GitHub stars
866
Token cost
~2.1k tokens
SKILL.md length
1,144 words
Files
1
Skills in repo
7
Repo updated
First seen
Licence
MIT

At a glance

Project code quality and architecture expectations for implementation, refactoring, planning, and code review.

  • Planning production code
  • SKILL.md covers Values we optimize for, How to apply this during coding and Review checklist
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Architecture in this repository

What it does

Code Quality Architecture is an agent skill from jmfederico/pi-web. Project code quality and architecture expectations for implementation, refactoring, planning, and code review. Use this skill whenever writing, modifying, reviewing, or planning production code or architecture in this repository, especially when making architecture choices, introducing modules/services/components, managing side effects, dependencies, state, or boundaries. Favor composable, contained, intention-revealing, separated, dependency-injected, testable code while respecting the idioms of the framework or…

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Code quality and Refactoring. The repository describes itself as: Web UI for Pi Coding Agent that keeps sessions alive in real workspaces. The licence is MIT.

When your agent uses it

  • Planning production code
  • Architecture in this repository
  • Especially when making architecture choices
  • Introducing modules/services/components

Example prompts

  • “/code-quality-architecture”

What it can do on your machine

Read from SKILL.md and the folder at commit 15c13a4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Code Quality Architecture loads about 2.1k tokens when it runs. Until then it costs about 140 tokens; SKILL.md has 1,144 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~140
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jmfederico/pi-web at commit 15c13a4, republished under its MIT licence (© jmfederico). 1,144 words, ~2,130 tokens.

Download SKILL.mdSave it as .claude/skills/code-quality-architecture/SKILL.md (or your agent's skills folder).
name
code-quality-architecture
description
Project code quality and architecture expectations for implementation, refactoring, planning, and code review. Use this skill whenever writing, modifying, reviewing, or planning production code or architecture in this repository, especially when making architecture choices, introducing modules/services/components, managing side effects, dependencies, state, or boundaries. Favor composable, contained, intention-revealing, separated, dependency-injected, testable code while respecting the idioms of the framework or library in use.

Code quality and architecture expectations

Use this skill as a design lens, not as a framework tutorial. The goal is to shape code so future agents and humans can understand it, change it safely, and test it without needing to reverse-engineer hidden coupling.

For test-specific strategy, test helper conventions, and UI test harness choices, use the testing-guide skill. This skill still treats testability as a production-code design concern.

Respect the project's existing conventions and the framework/library idioms already in use. If a dependency expects a particular pattern, such as inheritance, decorators, lifecycle hooks, or a registration API, use that pattern deliberately and keep the surrounding project code as simple and composable as possible.

Values we optimize for

Proportionate

Start with the simplest design that meets the behavioral contract and finish line. Prefer boring, local changes that solve the problem without surprising future maintainers.

When an edge case or race is identified, assess its plausible frequency and consequence before adding special handling. Address it now when the contract requires it, it is reasonably likely in normal use, or its impact justifies the added complexity. Otherwise defer special handling, rely on ordinary observable failure or recovery behavior, and revisit if real usage shows that the case matters. Do not defer cases with a credible risk of corrupting durable state, weakening a security or authorization boundary, or failing silently without a practical recovery path.

Avoid unrelated refactoring, opportunistic cleanup, and broad rewrites unless the task requires them. Avoid new abstractions that add ceremony without clarifying ownership, reducing duplication, isolating volatility, or improving testability.

Composable

Build behavior from small pieces with explicit contracts. Prefer functions, modules, factories, services, components, or adapters that can be combined without knowing each other's internals.

Prefer composition over inheritance. Reach for inheritance only when a framework/dependency requires it, when it clearly models a stable relationship, or when it is already the local convention. If you use inheritance, keep the hierarchy shallow and explain the reason in the design or final summary.

Contained

A unit of code should do its job without leaking state, assumptions, or side effects across the system. Keep effects at clear boundaries: network, filesystem, timers, process state, browser APIs, storage, logging, telemetry, and UI/event dispatch.

Make state ownership explicit: who owns it, who may mutate it, when it is created, and how it is cleaned up. Avoid hidden global coordination, surprise mutation, ad hoc event dispatch, and imports that perform work merely by being loaded. If code must produce side effects, make the trigger, scope, cleanup, and failure behavior visible.

Clear intention

Names, types, file boundaries, and function boundaries should reveal why the code exists. Prefer a small amount of clear structure over clever compactness.

Use types to express domain meaning, valid states, and boundaries between parts of the system. Do not duplicate lint/type rules here; the point is to make the design easier to understand, not merely to satisfy TypeScript.

Comments are most valuable when they explain why a decision exists, what invariant must be preserved, or why an apparent simpler approach would be unsafe. Avoid comments that merely restate the code.

Clear separation of concerns

Keep domain decisions, orchestration, framework glue, persistence, transport, rendering, and validation separate when that separation makes the code easier to reason about.

Framework-facing code should usually be thin: gather inputs, call the core logic, map results back to the framework. Core logic should usually be usable without starting the UI, server, session runtime, browser, filesystem, or network.

Deliberate error handling

Failures must be observable and traceable to their cause. Handle them at meaningful boundaries through an explicit return or throw, contextual logging, a user-visible error, or another signal appropriate to that boundary. Do not silently rescue failures, swallow errors, or turn them into vague fallback or success behavior. Avoid scattering defensive try/catch blocks everywhere; let core logic communicate failures clearly, then translate them at the edge that has the right context.

When changing PI WEB-managed durable state, structure operations so failure does not silently leave partial writes, ambiguous overwrites, or broken invariants. Apply this where an actual persistence or lifecycle boundary warrants it; do not add transactional machinery to ephemeral or reconstructible state without a concrete need.

Security and authorization boundaries fail closed. Never convert a validation, authentication, authorization, or policy failure into permissive behavior merely to keep an operation running.

Show full SKILL.md (422 more words)Show less
Dependencies injected

Pass collaborators, configuration, clocks, random sources, storage, network clients, and environment-specific services in through parameters, constructors, or small factories where practical. This makes dependencies visible and replaceable.

Do not introduce a heavy dependency-injection framework unless the project already uses one or there is a clear reason. Lightweight dependency injection is enough: explicit inputs beat hidden imports and singletons.

Testable by design

Testability should emerge from the previous values. Prefer pure or mostly pure core logic, small adapters around side effects, and explicit seams where tests can provide fakes or fixtures.

If a change is hard to test, treat that as design feedback. Look for hidden dependencies, mixed concerns, or side effects happening too deep in the call stack. Avoid designs that require excessive mocking just to reach the behavior under test.

How to apply this during coding

Before implementing, briefly identify the boundary you are changing:

  • What is the core behavior?
  • What are the side effects or external dependencies?
  • Who owns any mutable state, and how is it cleaned up?
  • Where should errors be handled or translated?
  • What should stay framework-specific, and what can be plain logic?
  • What would make this easy to test?

During implementation:

  • Keep the smallest useful public surface.
  • Prefer explicit inputs/outputs over ambient state.
  • Avoid work at import time; make startup, registration, listeners, timers, and connections explicit.
  • Use existing project patterns unless they conflict with these values strongly enough to justify a small refactor.
  • Avoid broad rewrites when a contained change will solve the problem.
  • Add abstraction only when it makes the code easier to change, test, or understand.
  • If you make an architectural tradeoff, mention it briefly in the final response.

Review checklist

When reviewing or finishing code, check:

  • Is this the simplest design that meets the behavioral contract and finish line, with any edge-case or race handling justified by likelihood or impact?
  • Can this behavior be reused or combined without copying internals?
  • Are side effects visible, bounded, and cleaned up when needed?
  • Is mutable state ownership clear?
  • Do names, types, and file boundaries communicate intent?
  • Are failures observable and traceable at the right boundary, without leaving durable state ambiguous or weakening a security or authorization boundary?
  • Are domain logic and framework glue separated enough for the size of the change?
  • Are important dependencies explicit and replaceable in tests?
  • Can the meaningful behavior be tested without booting unnecessary infrastructure?

Do not over-engineer small fixes. The right amount of architecture is the minimum structure that makes the code clear, safe to change, and straightforward to test.

© jmfederico, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/code-quality-architecture of jmfederico/pi-web.

Open the folder on GitHubat commit 15c13a4

Compare with similar skills

Code Quality Architecture next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Code Quality Architecture compared with similar skills
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Code Quality Architecture this skilljmfederico/pi-web866—~2.1kAutomated safety check: PassMIT
Systematic Code Refactoringluongnv89/claude-howto42k—~3kAutomated safety check: PassMIT
Ponytail Lazy Developer ModeDietrichGebert/ponytail158k—~871Automated safety check: PassMIT
Dignified Python Standardsdocling-project/docling69k—~1.5kAutomated safety check: PassApache-2.0
Clean Code GuardamElnagdy/guard-skills1.3k2 repos~4.3kAutomated safety check: PassMIT
Code Refactoring Workflowluongnv89/claude-howto42k—~3.1kAutomated safety check: PassMIT

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Categories

Questions about Code Quality Architecture

What does Code Quality Architecture do?

Project code quality and architecture expectations for implementation, refactoring, planning, and code review. Code Quality Architecture is an agent skill from jmfederico/pi-web. Project code quality and architecture expectations for implementation, refactoring, planning, and code review.

When should I use Code Quality Architecture?

Code Quality Architecture fits situations like: planning production code; architecture in this repository; especially when making architecture choices; introducing modules/services/components.

How do I install Code Quality Architecture in Claude Code?

Run `npx skills add jmfederico/pi-web --skill code-quality-architecture -a claude-code`. Or copy the skill folder (.agents/skills/code-quality-architecture in jmfederico/pi-web) into .claude/skills/code-quality-architecture in your project. Claude Code loads it when a task matches its description.

How do I install Code Quality Architecture in Codex?

Run `npx skills add jmfederico/pi-web --skill code-quality-architecture -a codex`. Or copy the skill folder (.agents/skills/code-quality-architecture in jmfederico/pi-web) into .agents/skills/code-quality-architecture in your project. Codex loads it when a task matches its description.

Can I use Code Quality Architecture in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jmfederico/pi-web --skill code-quality-architecture -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/code-quality-architecture, .gemini/skills/code-quality-architecture, .github/skills/code-quality-architecture and .opencode/skills/code-quality-architecture in your project.

What does Code Quality Architecture need to run?

SKILL.md names no scripts, command-line tools or credentials: Code Quality Architecture is instructions for the agent only.

Does Code Quality Architecture access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Code Quality Architecture safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Code Quality Architecture use?

Code Quality Architecture is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Code Quality Architecture use?

About 2.1k tokens (SKILL.md is roughly 8.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Code Quality Architecture?

Skills that share tags, products or a category with Code Quality Architecture: Systematic Code Refactoring (luongnv89/claude-howto, 42k stars), Ponytail Lazy Developer Mode (DietrichGebert/ponytail, 158k stars), Dignified Python Standards (docling-project/docling, 69k stars) and Clean Code Guard (amElnagdy/guard-skills, 1.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Code Quality Architecture?

jmfederico (a GitHub user) maintains it in jmfederico/pi-web, which has 866 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on October 6, 2026.

Source: jmfederico/pi-web on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.