porcupine-md

Validate frontend design in a real browser using the anoa CLI — screenshots, interactive snapshots, responsive, dark-mode and contrast checks.

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GitLab workflow automation with the glab CLI — merge requests, issues, CI, releases, and safe message escaping. Auth via GITLAB_TOKEN (set in global settings, attached to the sandbox env).

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Deterministic AI development workflow orchestrator. Manages task boards (.jonggrang/jonggrang-tasks.json), runs 16-phase pipelines (BUGFIX/SMALL/MEDIUM/LARGE), installs lifecycle hooks for Claude Code and OpenCode, and coordinates five specialist roles (Lead/Developer/Reviewer/TestLead/Tester). Use when planning features, executing multi-step development workflows, or orchestrating AI coding agents. Run via npx jonggrang.

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Used by the Reviewer agent during Phase 9 (DesignVerify) and Phase 11 (Quality) to evaluate frontend code. Assesses visual hierarchy, spacing consistency, accessibility, and detects formulaic 'AI slop' design patterns, providing actionable feedback to the Developer.

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Implement rate limiting on APIs. Per-IP, per-user, sliding window patterns. Express and framework-agnostic.

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Diagnose and fix flaky tests. Covers race conditions, timing issues, test pollution, async leaks.

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React performance optimization. Identify unnecessary renders, apply memo/useCallback/useMemo correctly.

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GitHub workflow automation with the gh CLI — pull requests, issues, releases, the REST/GraphQL API, and safe message escaping. Auth via GH_TOKEN (set in global settings, attached to the sandbox env).

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Unit testing patterns for backend and frontend. AAA structure, effective mocking, test isolation.

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Infrastructure-first security audit (OWASP, secrets, dependencies).

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Deep knowledge about deploying applications to Google Cloud Platform (Cloud Run, App Engine, Compute Engine).

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Systematic debugging methodology. Reproduce → Isolate → Hypothesize → Verify → Fix → Confirm.

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Deep knowledge about deploying applications to Fly.io (MicroVMs, Docker).

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Setup web app page with component, layout, data fetching, and tests

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Production-grade error handling for Node.js/TypeScript backends. Error classes, HTTP mapping, logging, retry strategies.

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Generate database migration, model update, and seed data

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Setup authentication flow (register, login, session/JWT, middleware)

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Route backend tasks to the right library skill. Detects intent and returns specific skill file paths to load.

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Used by the Lead agent during Phase 6 (Brainstorm) to collaboratively explore user intent, requirements, and alternative approaches before locking in the architecture. Helps turn raw ideas into fully formed specs through natural dialogue.

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Iteratively define problem and solution shapes.

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Route database tasks to the right library skill. Covers migrations, query optimization, ORM, transactions.

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16-phase feature orchestration workflow. Runs in the main thread as Kernel Mode. Coordinates the Lead→Developer→Reviewer→TestLead→Tester assembly line.

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Resume an interrupted orchestration run across Claude Code sessions using MANIFEST.yaml

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Identify independent failures and spawn concurrent agents. Turns sequential N×time into 1×time.

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