plankton-code-quality▌
affaan-m/everything-claude-code · updated Apr 8, 2026
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Write-time code quality enforcement with auto-formatting, linting, and Claude-powered subprocess fixes on every file edit.
- ›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
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) — 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:
- PreToolUse hook —
protect_linter_configs.shblocks edits to all linter configs before they happen - Stop hook —
stop_config_guardian.shdetects config changes viagit diffat session end - 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 (useuv)npm,yarn,pnpm→ Blocked (usebun)- 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:
- Copy
.claude/hooks/directory to your project - Copy
.claude/settings.jsonhook configuration - Copy linter config files (
.ruff.toml,biome.json, etc.) - 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, 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
- Install ECC as your plugin (agents, skills, commands, rules)
- Add Plankton hooks for write-time quality enforcement
- Use AgentShield for security audits
- 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 tiersubprocess_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:
- run formatter checks
- run lint/type checks
- fail fast on strict mode
- publish remediation summary
Health Metrics
Track:
- edits flagged by gates
- average remediation time
- repeat violations by category
- merge blocks due to gate failures
How to use plankton-code-quality on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add plankton-code-quality
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches plankton-code-quality from GitHub repository affaan-m/everything-claude-code and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate plankton-code-quality. Access the skill through slash commands (e.g., /plankton-code-quality) or your agent's skill management interface.
Security & Verification Notice
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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
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
Competitive Analysis
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
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
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
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ 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.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★51 reviews- ★★★★★Mateo Bansal· Dec 28, 2024
I recommend plankton-code-quality for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Ganesh Mohane· Dec 12, 2024
plankton-code-quality reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Ava Brown· Dec 12, 2024
Registry listing for plankton-code-quality matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Isabella Gonzalez· Dec 8, 2024
Useful defaults in plankton-code-quality — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Ren Rahman· Nov 27, 2024
Registry listing for plankton-code-quality matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Omar Menon· Nov 19, 2024
plankton-code-quality reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Rahul Santra· Nov 3, 2024
I recommend plankton-code-quality for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Omar Mehta· Nov 3, 2024
Useful defaults in plankton-code-quality — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Pratham Ware· Oct 22, 2024
Useful defaults in plankton-code-quality — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Ava Chen· Oct 22, 2024
I recommend plankton-code-quality for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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