ECC/skills/plankton-code-quality/SKILL.md

name, description, metadata

name	description	metadata
plankton-code-quality	Write-time code quality enforcement using Plankton — auto-formatting, linting, and Claude-powered fixes on every file edit via hooks. Use when setting up write-time formatting, linting, or auto-fix hooks on file edits.	origin community

Plankton Code Quality Skill

Integration reference for Plankton (credit: @alxfazio), a write-time code quality enforcement system for Claude Code. Plankton runs formatters and linters on every file edit via PostToolUse hooks, then spawns Claude subprocesses to fix violations the agent didn't catch.

When to Use

• You want automatic formatting and linting on every file edit (not just at commit time)
• You need defense against agents modifying linter configs to pass instead of fixing code
• You want tiered model routing for fixes (Haiku for simple style, Sonnet for logic, Opus for types)
• You work with multiple languages (Python, TypeScript, Shell, YAML, JSON, TOML, Markdown, Dockerfile)

How It Works

Three-Phase Architecture

Every time Claude Code edits or writes a file, Plankton's multi_linter.sh PostToolUse hook runs:

Phase 1: Auto-Format (Silent)
├─ Runs formatters (ruff format, biome, shfmt, taplo, markdownlint)
├─ Fixes 40-50% of issues silently
└─ No output to main agent

Phase 2: Collect Violations (JSON)
├─ Runs linters and collects unfixable violations
├─ Returns structured JSON: {line, column, code, message, linter}
└─ Still no output to main agent

Phase 3: Delegate + Verify
├─ Spawns claude -p subprocess with violations JSON
├─ Routes to model tier based on violation complexity:
│   ├─ Haiku: formatting, imports, style (E/W/F codes) — 120s timeout
│   ├─ Sonnet: complexity, refactoring (C901, PLR codes, oxlint complexity) — 300s timeout
│   └─ Opus: type system, deep reasoning (unresolved-attribute) — 600s timeout
├─ Re-runs Phase 1+2 to verify fixes
└─ Exit 0 if clean, Exit 2 if violations remain (reported to main agent)

What the Main Agent Sees

Scenario	Agent sees	Hook exit
No violations	Nothing	0
All fixed by subprocess	Nothing	0
Violations remain after subprocess	[hook] N violation(s) remain	2
Advisory (duplicates, old tooling)	[hook:advisory] ...	0

The main agent only sees issues the subprocess couldn't fix. Most quality problems are resolved transparently.

Config Protection (Defense Against Rule-Gaming)

LLMs will modify .ruff.toml or biome.json to disable rules rather than fix code. Plankton blocks this with three layers:

1. PreToolUse hook — protect_linter_configs.sh blocks edits to all linter configs before they happen
2. Stop hook — stop_config_guardian.sh detects config changes via git diff at session end
3. Protected files list — .ruff.toml, biome.json, .shellcheckrc, .yamllint, .hadolint.yaml, and more

Package Manager Enforcement

A PreToolUse hook on Bash blocks legacy package managers:

• pip, pip3, poetry, pipenv → Blocked (use uv)
• npm, yarn, pnpm → Blocked (use bun)
• Allowed exceptions: npm audit, npm view, npm publish

Setup

Quick Start

Note: Plankton requires manual installation from its repository. Review the code before installing.

# Install core dependencies
brew install jaq ruff uv

# Install Python linters
uv sync --all-extras

# Start Claude Code — hooks activate automatically
claude

No install command, no plugin config. The hooks in .claude/settings.json are picked up automatically when you run Claude Code in the Plankton directory.

Per-Project Integration

To use Plankton hooks in your own project:

1. Copy .claude/hooks/ directory to your project
2. Copy .claude/settings.json hook configuration
3. Copy linter config files (.ruff.toml, biome.json, etc.)
4. Install the linters for your languages

Language-Specific Dependencies

Language	Required	Optional
Python	ruff, uv	ty (types), vulture (dead code), bandit (security)
TypeScript/JS	biome; oxlint (>= 1.37.0) when using complexity	semgrep, knip (dead exports)
Shell	shellcheck, shfmt	—
YAML	yamllint	—
Markdown	markdownlint-cli2	—
Dockerfile	hadolint (>= 2.12.0)	—
TOML	taplo	—
JSON	jaq	—

Pairing with ECC

Complementary, Not Overlapping

Concern	ECC	Plankton
Code quality enforcement	PostToolUse hooks (Prettier, tsc)	PostToolUse hooks (20+ linters + subprocess fixes)
Security scanning	AgentShield, security-reviewer agent	Bandit (Python), Semgrep (TypeScript)
Config protection	—	PreToolUse blocks + Stop hook detection
Package manager	Detection + setup	Enforcement (blocks legacy PMs)
CI integration	—	Pre-commit hooks for git
Model routing	Manual (/model opus)	Automatic (violation complexity → tier)

Recommended Combination

1. Install ECC as your plugin (agents, skills, commands, rules)
2. Add Plankton hooks for write-time quality enforcement
3. Use AgentShield for security audits
4. Use ECC's verification-loop as a final gate before PRs

Avoiding Hook Conflicts

If running both ECC and Plankton hooks:

• ECC's Prettier hook and Plankton's biome formatter may conflict on JS/TS files
• Resolution: disable ECC's Prettier PostToolUse hook when using Plankton (Plankton's biome is more comprehensive)
• Both can coexist on different file types (ECC handles what Plankton doesn't cover)

Configuration Reference

Plankton's .claude/hooks/config.json controls all behavior:

{
  "languages": {
    "python": true,
    "shell": true,
    "yaml": true,
    "json": true,
    "toml": true,
    "dockerfile": true,
    "markdown": true,
    "typescript": {
      "enabled": true,
      "js_runtime": "auto",
      "biome_nursery": "warn",
      "semgrep": true
    }
  },
  "phases": {
    "auto_format": true,
    "subprocess_delegation": true
  },
  "subprocess": {
    "tiers": {
      "haiku":  { "timeout": 120, "max_turns": 10 },
      "sonnet": { "timeout": 300, "max_turns": 10 },
      "opus":   { "timeout": 600, "max_turns": 15 }
    },
    "volume_threshold": 5
  }
}

Key settings:

• Disable languages you don't use to speed up hooks
• volume_threshold — violations > this count auto-escalate to a higher model tier
• subprocess_delegation: false — skip Phase 3 entirely (just report violations)

Environment Overrides

Variable	Purpose
HOOK_SKIP_SUBPROCESS=1	Skip Phase 3, report violations directly
HOOK_SUBPROCESS_TIMEOUT=N	Override tier timeout
HOOK_DEBUG_MODEL=1	Log model selection decisions
HOOK_SKIP_PM=1	Bypass package manager enforcement

References

• Plankton (credit: @alxfazio)
• Plankton REFERENCE.md — Full architecture documentation (credit: @alxfazio)
• Plankton SETUP.md — Detailed installation guide (credit: @alxfazio)

ECC v1.8 Additions

Copyable Hook Profile

Set strict quality behavior:

export ECC_HOOK_PROFILE=strict
export ECC_QUALITY_GATE_FIX=true
export ECC_QUALITY_GATE_STRICT=true

Language Gate Table

• TypeScript/JavaScript: Biome preferred, Prettier fallback
• Python: Ruff format/check
• Go: gofmt

Config Tamper Guard

During quality enforcement, flag changes to config files in same iteration:

• biome.json, .eslintrc*, prettier.config*, tsconfig.json, pyproject.toml

If config is changed to suppress violations, require explicit review before merge.

CI Integration Pattern

Use the same commands in CI as local hooks:

1. run formatter checks
2. run lint/type checks
3. fail fast on strict mode
4. publish remediation summary

Health Metrics

Track:

• edits flagged by gates
• average remediation time
• repeat violations by category
• merge blocks due to gate failures

---

Gabe's addition: oxlint complexity + ratchet ceiling (JS/TS)

Closes the JS/TS gap in the model-routing table above. Python complexity (ruff C901, PLR) already routes to Sonnet. JS/TS had no equivalent rule turned on by default.

Turn on oxlint's complexity rule when using it

oxlint's complexity rule (source: eslint's complexity rule, ported) lives in the "restriction" category, which oxlint does not enable by default. It must be turned on by hand. Verified against https://oxc.rs/docs/guide/usage/linter/rules/eslint/complexity (2026-08-27): default option is max: 20. The rule is available in oxlint >= 1.37.0.

The skill's Language-Specific Dependencies table keeps oxlint optional for TypeScript/JS generally. When adopting the complexity rule, use oxlint >= 1.37.0 and treat it as a required dependency. Add the rule to the supported oxlint configuration the project already uses (.oxlintrc.json, .oxlintrc.jsonc, oxlint.config.ts, or oxlint.config.mts). If none exists, create one; do not create a second configuration file in the same directory.

Measure the codebase's current worst complexity score before choosing the initial enforced ceiling. The template below is intentionally incomplete: replace <MEASURED_CEILING> with that score, optionally plus a small amount of headroom, before committing the "error" gate. Oxlint's default of 20 is a long-term target, not a safe universal starting ceiling.

{
  "rules": {
    "complexity": ["error", { "max": "<MEASURED_CEILING>" }]
  }
}

Replace the placeholder before running oxlint; it is not a valid numeric threshold until the repository has been measured. See the ratchet section below for how the ceiling gets set on a real codebase.

Model-routing row

Add oxlint complexity violations to the same row as the existing Python entry in the Phase 3 subprocess table:

├─ Sonnet: complexity, refactoring (C901, PLR codes, oxlint complexity), 300s timeout

Same tier as Python's C901/PLR. A complexity violation is a refactoring job either way, language does not change the model tier.

The ratchet-ceiling technique

Source: https://github.com/modem-dev/hunk/pull/861 (merged 2026-08-26, verified against the PR's own diff and description via the GitHub API, not paraphrased from memory). Hunk turned on oxlint's complexity rule with "error", { "max": 80 } in .oxlintrc.json. Their own worst score at the time was 78 (App), next was 76 (validateFileViewLayout). From the PR body: "This is intentionally an initial regression ceiling rather than the long-term target... so 80 adds enforcement without grandfathering or suppressions. The ceiling can be ratcheted downward as existing hotspots are simplified." And: "A global ceiling does not prevent a function below 80 from growing toward it."

The technique, as actually run in that PR:

1. Measure the current worst complexity score in the codebase (oxlint reports it when the rule fires).
2. Set the ENFORCED ceiling to a value at least as high as that worst score, not to oxlint's own default of 20. Add a small amount of headroom if needed so the initial enable does not fail CI on a score you have not fixed yet (hunk used 80 against a worst of 78).
3. Commit that as "error", wired into the existing lint CI step. This is a real gate from the first commit, not a suggestion.
4. Never grandfather. The ceiling is global. A function sitting at 40 today is not exempt, it still cannot cross the ceiling later. That is the whole point: catch growth, not just today's worst offenders.
5. Never blanket-suppress. No per-file or per-function disable comments to make a violation go away. Fix it or leave it under the ceiling.
6. Each time a flagged hotspot is refactored below the ceiling, re-measure the global maximum across the whole codebase. Lower the ceiling by hand only to a value that remains at least as high as every remaining function's score (plus any deliberate headroom). This is a manual step done as its own commit, not automated. It is how the ceiling moves toward the linter's real default of 20 over time instead of sitting at the codebase's worst score forever.

One caveat, stated plainly: the PR itself went straight from "rule off" to "error" enforcement in one commit. It did not stage through a report-only or warn-only phase first. Starting with the rule set to "warn" for one CI run before flipping it to "error" is a reasonable staging step if a team has never measured its own worst score and does not want a surprise CI failure, but that staging step is Gabe's own prudent practice, not something verified in hunk's PR. Say so if you use it, do not attribute it to the source.