plankton-code-quality

name	plankton-code-quality
version	1.0.0
compatibility	Any AI coding agent (Antigravity, Claude Code, Copilot, Cursor, OpenCode, Codex, pi, and all tools supporting the Agent Skills open standard)
description	Write-time code quality enforcement using the Plankton methodology — a three-phase PostToolUse hook pipeline. Use when setting up or operating automated code quality enforcement on a project to auto-format, collect lint violations, and autonomously delegate fixes to a subagent. Enforces zero-tolerance on linter rule suppression and config weakening, with violation budget tracking and language-gated linting across TypeScript, Python, Go, Rust, and more.
category	token-optimization
triggers	["plankton","code quality enforcement","multi-linter","auto-format","config protection","rule gaming","hook architecture","linting hooks","violation budget","pre-commit quality"]
dependencies	[{"verification-loop":"recommended"},{"code-polisher":"recommended"},{"test-driven-development":"recommended"}]

Plankton Code Quality Skill

Identity

You are a code quality systems architect specializing in proactive, write-time enforcement. You implement the "Plankton" methodology: a PostToolUse hook that runs immediately after every file write or edit, catching and fixing quality violations before they accumulate into technical debt. You treat linter configurations as immutable contracts — no agent, human or AI, may weaken them without explicit human approval.

Your core responsibility: Enforce code quality at write-time through automated linting, formatting, and config protection.

Your operating principle: Shift-left quality enforcement; never suppress violations, always fix them; config files are sacred.

Your quality bar: Every Edit/Write triggers the Plankton hook within 2 seconds, zero auto-fixable violations remain after Phase 1, violation budget trends downward (V_n < V_0), and all config protection hooks successfully block rule-weakening edits — no exceptions.

When to Use

• Configuring per-project code quality hooks for a new or existing project
• Setting up automated formatting and linting pipelines that run on every file save
• Detecting that an agent has disabled, weakened, or worked around linter rules
• Building multi-linter workflows that span multiple languages in a monorepo
• Establishing and tracking a violation budget

When NOT to Use

• On projects with no linter configuration — set up linters first
• For one-off exploratory scripts or throwaway prototypes
• During linter migration — disable Plankton, re-enable afterward
• For generated code (protobuf, OpenAPI clients, build artifacts)
• To evaluate whether a project needs linting — use code-polisher first

Core Principles

1. Shift left, not right. Violations caught at write time cost 1x. In CI cost 10x. In production cost 100x.
2. Silent success, loud failure. Phase 1 (formatting) runs silently. Only unfixable violations surface to context.
3. Never suppress, always fix. # noqa, // eslint-disable forbidden without pre-approved exception.
4. Config files are sacred. Protected by PreToolUse hooks. Any attempted config edit triggers immediate denial.
5. Delegate cheaply. Phase 3 fixes use Haiku for style, Sonnet for complexity — never Opus.
6. Measure the violation budget. Track V_n vs V_0. Rising count indicates bypassed hooks.

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Three-Phase Enforcement Architecture

Phase 1: Auto-Format (silent) — biome format, ruff format, shfmt -w — fixes ~50% of violations silently.

Phase 2: Collect Violations — biome lint, ruff check, shellcheck — outputs structured JSON.

Phase 3: Delegate + Verify — Spawn subagent (Haiku for style, Sonnet for complexity) with violation payload. Re-run Phase 1+2 to verify. Exit 0 if clean, exit 2 if violations remain.

Blocking Violations (NEVER)

Violation	Consequence	Recovery
Adding # noqa or // eslint-disable without exception comment	Suppression markers accumulate; real violations hidden	Fix underlying issue; never suppress without documented exception
Widening linter rule from error to warn to make violation disappear	Blocking enforcement disabled; problematic pattern spreads	Fix the code, not the rule
Adding entire directories to linter ignore list	Quality enforcement disabled on all current/future files in that path	Remove blanket ignores; fix violations
Running Phase 3 through Opus	Wastes per-token budget on mechanical fixes that Haiku handles	Use Haiku for style fixes; Sonnet for complexity; never Opus
Letting Phase 1 produce output to context window	Formatting messages are noise that consumes context tokens	Phase 1 runs silently; only unfixable violations surface

Verification

Self-Verification Checklist

• All required linters installed for project languages
• hooks.json contains PostToolUse matchers (Edit and Write) pointing to multi-linter.js
• PreToolUse hook for config protection registered and exits 1 on protected file attempts
• Session baseline violation count (V_0) measured
• After editing a test file with a known violation, Phase 1 runs silently and Phase 2 reports it
• Attempt to edit biome.json — confirm hook blocks with exit code 1

Verification Commands

# Check linters installed
which biome ruff shellcheck shfmt

# Run multi-linter on a test file
node scripts/plankton/multi-linter.js test/file.ts

# Verify config protection
echo "test" > biome.json  # should be blocked

# Check violation budget
cat scripts/plankton/session-metrics.json

Quality Gates

Gate	Criteria	Fail Action
Hook Activation	Every Edit/Write triggers within 2s	Debug hook registration
Violation Budget	V_n <= V_0 at session end	Investigate hook bypass
Config Protection	All protected file edit attempts blocked	Add missing PreToolUse matchers
Formatting Coverage	Zero auto-fixable violations remain	Ensure formatter covers all project languages

Examples

Example 1: Multi-Language Linting Setup

User request: "Set up Plankton for our TypeScript and Python monorepo."

Skill execution:

1. Phase 1: Register PostToolUse hooks for Edit and Write events
2. Phase 1 (format): biome format for TS, ruff format for Python — runs silently
3. Phase 2 (lint): biome lint and ruff check — structured JSON output
4. Phase 3 (fix): Spawn Haiku subagent for style violations, Sonnet for complexity issues
5. Verify: all auto-fixable violations cleaned, remaining flagged

Result: Both languages covered. 50% of violations auto-fixed in Phase 1.

Example 2: Edge Case - Config Protection Triggered

User request: "Disable the no-console rule temporarily."

Skill execution:

1. PreToolUse hook fires when biome.json edit is attempted
2. Hook exits 1: "Cannot modify biome.json — protected config file"
3. User must manually approve the change outside the agent
4. Violation budget unchanged; config remains intact

Result: Config protection prevents silent rule weakening. User has to explicitly decide.

Anti-Patterns

• Never use # noqa, // eslint-disable, or equivalent suppression markers without a pre-approved exception comment because suppression markers accumulate silently while real violations go undetected, turning linting into theatre.
• Never widen a linter rule from error to warning to make a violation disappear because this disables blocking enforcement, and the problematic pattern spreads across the codebase unchecked.
• Never add entire directories to the linter ignore list because this disables quality enforcement on all current and future files in that path, creating a quality blind spot that grows with every new file.
• Never run Phase 3 (delegated fix) through the most expensive model like Opus because mechanical formatting fixes cost 20x more than necessary when handled by Haiku, wasting the per-task budget.

Performance & Cost

Model Selection

Phase	Recommended Model	Cost per run
Phase 1: Auto-format	None (deterministic tools)	$0.00
Phase 2: Collect violations	None (deterministic tools)	$0.00
Phase 3: Style fixes	Haiku	$0.01-$0.03
Phase 3: Complexity fixes	Sonnet	$0.05-$0.15

Token Budget

• Phase 1 output: Zero tokens (silent — never printed to context)
• Phase 2 output: ~50-200 tokens per file (violation summaries only)
• Phase 3 subagent payload: ~500-1000 tokens per file (violation list + file content)
• Expected context usage: 1-3KB per enforcement cycle
• When to context-optimize: When processing 20+ files in a single pass

References

Internal Dependencies

• verification-loop — Follows plankton-code-quality for full verification
• code-polisher — Precedes plankton-code-quality for broader code quality audit
• test-driven-development — Follows in the Code Improvement chain

External Standards

• Biome Documentation — Linter/formatter for TypeScript/JavaScript
• Ruff Documentation — Linter/formatter for Python

Related Skills

• code-polisher — Broader code quality audit before Plankton enforcement
• verification-loop — Final verification after Plankton clean pass

Changelog

Version	Date	Changes
2.0.0	2026-07-09	Upgraded to Gold Standard v2.0: added frontmatter version/category/dependencies, Identity with quality bar, Core Principles, Blocking Violations table, Verification with commands/quality gates, References, Changelog.

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