Web・iOS・Androidの画面を、読み上げやキーボード操作に対応させ、ラベル、配色、操作対象の大きさなどをWCAG 2.2に沿って設計・点検するスキル。
- アイコンボタンの説明を付けたいとき
- キーボード操作とモーダルの点検
- コントラストや操作対象の大きさの確認
Claude Codeのファイル編集時に、Planktonで自動整形とコード検査を行う設定を支援するスキル。残った違反の自動修正や再検査、検査ルールの保護も扱います。
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.
Claude Codeでファイルを編集するたびに、Planktonで自動整形とlint(コードの問題を見つける静的検査)を実行する設定を支援します。残った違反はClaudeの別プロセスへ渡し、内容の複雑さに応じてHaiku、Sonnet、Opusに振り分けます。修正後は再検査し、解消しない問題を元のエージェントへ返します。検査設定の改変を防ぐ仕組みや、CIで同じ検査を行う方法も扱います。
コミット時だけでなく、編集の直後に書式や品質を確認したい場合に向いています。Python、TypeScript、Shellなど複数の言語を扱うプロジェクトや、コード修正の代わりに検査ルールが緩められるのを防ぎたい場合にも使えます。
Planktonは手動で導入し、利用前にコードを確認する前提です。Claude Codeと、対象言語ごとの整形・検査ツールが必要です。標準のフックはPythonにuv、JavaScriptにbunを使うよう制限します。ECCと併用する場合はPrettierとbiomeの競合に注意が必要です。TypeScript/JSの複雑さの検査にはoxlint 1.37.0以上を使い、実測した値で上限を設定します。
この紹介文は、公開されている SKILL.md をもとに AI(Claude Haiku)が作成しました。正確な仕様は下の原文を確認してください。
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, 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)
| 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 publishNote: 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.
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 (>= 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 | — |
| 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:
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.
complexity rule when using itoxlint'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 Oxlint's complexity rule
(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.
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.
Source: Hunk PR #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:
"error", wired into the existing lint CI step. This is a real gate
from the first commit, not a suggestion.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.
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
Web・iOS・Androidの画面を、読み上げやキーボード操作に対応させ、ラベル、配色、操作対象の大きさなどをWCAG 2.2に沿って設計・点検するスキル。
AIエージェントの不調を、指示・記憶・ツール実行・画面表示など12の層から調べるスキル。コードやログを根拠に原因を整理し、重要度順の指摘と修正案をまとめます。
実際の開発課題で複数のコーディングエージェントを比較するスキル。成功率、取得可能なAPI費用、所要時間、繰り返し実行の安定性を測り、選定や更新後の評価に使えます。
AIエージェントが使うツールの種類や入出力、エラーからの復帰手順を設計・見直します。文脈の情報量も整理し、作業完了率や再試行回数で改善を評価します。
AIエージェントの失敗や同じ操作の繰り返しを記録し、原因の切り分け、小さな復旧操作、結果の報告まで進める手順を示して、根拠のある再試行につなげるスキル。
AIエージェントが失敗や同じ操作を繰り返す原因を、エラーと実行状況から整理します。小さな復旧操作を試し、結果と根拠を引き継げる報告にまとめるスキルです。