Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
日本語の概要は準備中です。原文の説明を表示しています。
Write-time code quality enforcement using Plankton — auto-formatting, linting, and Claude-powered fixes on every file edit via hooks.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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.
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) — 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)
| 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.
LLMs will modify .ruff.toml or biome.json to disable rules rather than fix code. Plankton blocks this with three layers:
protect_linter_configs.sh blocks edits to all linter configs before they happenstop_config_guardian.sh detects config changes via git diff at session end.ruff.toml, biome.json, .shellcheckrc, .yamllint, .hadolint.yaml, and moreA PreToolUse hook on Bash blocks legacy package managers:
pip, pip3, poetry, pipenv → Blocked (use uv)npm, yarn, pnpm → Blocked (use bun)npm audit, npm view, npm publish# Clone Plankton into your project (or a shared location)
# Note: Plankton is by @alxfazio
git clone https://github.com/alexfazio/plankton.git
cd plankton
# 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.
To use Plankton hooks in your own project:
.claude/hooks/ directory to your project.claude/settings.json hook configuration.ruff.toml, biome.json, etc.)| Language | Required | Optional |
|---|---|---|
| Python | ruff, uv | ty (types), vulture (dead code), bandit (security) |
| TypeScript/JS | biome | oxlint, semgrep, knip (dead exports) |
| Shell | shellcheck, shfmt | — |
| YAML | yamllint | — |
| Markdown | markdownlint-cli2 | — |
| Dockerfile | hadolint (>= 2.12.0) | — |
| TOML | taplo | — |
| JSON | jaq | — |
| 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) |
If running both ECC and Plankton hooks:
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:
volume_threshold — violations > this count auto-escalate to a higher model tiersubprocess_delegation: false — skip Phase 3 entirely (just report violations)| 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 |
Set strict quality behavior:
export ECC_HOOK_PROFILE=strict
export ECC_QUALITY_GATE_FIX=true
export ECC_QUALITY_GATE_STRICT=true
During quality enforcement, flag changes to config files in same iteration:
biome.json, .eslintrc*, prettier.config*, tsconfig.json, pyproject.tomlIf config is changed to suppress violations, require explicit review before merge.
Use the same commands in CI as local hooks:
Track:
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
日本語の概要は準備中です。原文の説明を表示しています。
Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.
日本語の概要は準備中です。原文の説明を表示しています。
Engineering operating model for teams where AI agents generate a large share of implementation output.
日本語の概要は準備中です。原文の説明を表示しています。
Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns.
日本語の概要は準備中です。原文の説明を表示しています。
REST API design patterns including resource naming, status codes, pagination, filtering, error responses, versioning, and rate limiting for production APIs.
日本語の概要は準備中です。原文の説明を表示しています。
Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.
日本語の概要は準備中です。原文の説明を表示しています。