Write-time code quality enforcement with auto-formatting, linting, and Claude-powered subprocess fixes on every file edit.
Works with
Three-phase architecture: silent auto-formatting, violation collection, and tiered model routing (Haiku for style, Sonnet for complexity, Opus for types) to fix unfixable issues
Supports Python, TypeScript, Shell, YAML, JSON, TOML, Markdown, and Dockerfile with 20+ linters including ruff, biome, shellcheck, and hadolint
Config protection via PreToolUse and Stop h
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionplankton-code-qualityExecute the skills CLI command in your project's root directory to begin installation:
Fetches plankton-code-quality from affaan-m/everything-claude-code and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate plankton-code-quality. Access via /plankton-code-quality in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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 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, 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:
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
asyrafhussin/agent-skills
shadcn/improve
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
I recommend plankton-code-quality for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
plankton-code-quality reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for plankton-code-quality matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in plankton-code-quality — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for plankton-code-quality matched our evaluation — installs cleanly and behaves as described in the markdown.
plankton-code-quality reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend plankton-code-quality for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in plankton-code-quality — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Useful defaults in plankton-code-quality — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend plankton-code-quality for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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