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技能库 智客分类:Agent 工作流 plankton-code-quality

Plankton Code Quality

使用"浮游生物"(Plankton)的写出时间代码质量执行——通过钩子编辑的每个文件上自动格式化,linting,和克勞德能修正. 在文件编辑中设置写时格式化,林入,或自动固定钩子时使用.

10486 安装量

官方网址:skills.sh

技能介绍

先看中文介绍;官方 description 原文单独保留,不改写 SKILL.md。

做什么

使用 Plankton —— 自动格式化、 linting 和 Claude 驱动的修改来编辑每个文件的质量

何时用

- 说吧 您想要在每个文件编辑上自动格式化并林入( 不仅仅是在承诺时)

代理如何加载

按 Agent Skills 渐进披露:启动时只加载 name 与 description(约 100 token);任务匹配后才读入整份 SKILL.md 正文;scripts/、references/、assets/ 仅在需要时再读。 本文件正文结构:Plankton Code Quality Skill、When to Use、How It Works、Three-Phase Architecture、What the Main Agent Sees、Config Protection (Defense Against Rule-Gaming)。

文件分析

文件分析:这是一份仅含 SKILL.md 的指令型技能,代理激活后整份正文进入上下文。

官方 description(原文)

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.

Plankton Code Quality SkillWhen to UseHow It WorksThree-Phase ArchitectureWhat the Main Agent SeesConfig Protection (Defense Against Rule-Gaming)Package Manager EnforcementSetupQuick StartInstall core dependenciesInstall Python lintersStart Claude Code — hooks activate automatically

来源分类:skills.sh agent-skill

SKILL.md 与 Agent 调用

官方规范 ↗
name
plankton-code-quality
description
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.
  1. 发现技能客户端向 Agent 提供名称与描述目录。
  2. 匹配与调用用户指定或任务匹配后,载入 SKILL.md 指令。
  3. 按需加载按步骤读取参考文档、使用脚本与素材。

具体调用语法与可用工具以目标 Agent 客户端为准。 查看调用机制说明 ↗

安装这个技能

Skills CLI ↗

先选择目标 Agent 和安装范围,保留技能包的附属文件,安装后检查客户端能否发现该技能。

交给 Agent 安装

复制安装指令给支持 Agent Skills 的代理,确认其中的目标目录与客户端匹配。

把 Agent Skill「plankton-code-quality」安装到我的项目:SKILL.md 原文与官方 description 见 https://zicq.com/zh/skills/skl-da96b84aeacbd761-Plankton-Code-Quality.html
请存为 .cursor/skills/plankton-code-quality/SKILL.md 或 .claude/skills/plankton-code-quality/SKILL.md,frontmatter 的 name 与 description 保持原样,不要改写。

GitHub 完整包 ↗

终端安装 · Skills CLI

需要 Node.js 与 npx。先查看仓库技能列表,确认实际名称。

npx skills add 'https://github.com/affaan-m/ecc' --list

npx skills add 'https://github.com/affaan-m/ecc' --skill 'plankton-code-quality'

CLI 会交互选择目标 Agent,默认安装到项目;用户级安装使用 -g。先通过查看命令核对仓库内容,再用 npx skills list 检查已安装技能。

阅读排版
--- name: plankton-code-quality description: "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." metadata: 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. ```bash # 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: ```json { "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: ```bash 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 [Oxlint's complexity rule](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 `` 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. ```json { "rules": { "complexity": ["error", { "max": "" }] } } ``` 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: [Hunk PR #861](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.

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