By glowElephant
Complete AI coding workflow system. Self-correcting memory + persistent FTS5-indexed research wikis + auto-research loop + multi-LLM council on a single SQLite store. 33 skills, 8 agents, 22 commands, 37 hook scripts across 24 events. Cross-agent via SkillKit.
Surface patterns from your pro-workflow learnings and session history.
Auto-detect project type and configure quality gates, permissions, and hooks for a new codebase
Create a well-crafted commit after running pro-workflow quality checks.
Smart context compaction with state preservation — saves critical state before compact and restores after
Diagnose and fix context window problems.
Break down complex tasks into implementation plans before writing code. Use when task touches >5 files, requires architecture decisions, or has unclear requirements.
Code review specialist that verifies every finding against actual code before reporting. Use before committing, for PR reviews, or after major changes.
Confidence-gated exploration that assesses readiness before implementation. Scores 0-100 across five dimensions and gives GO/HOLD verdict.
Multi-phase development agent. Research > Plan > Implement with validation gates. Use PROACTIVELY when building features that touch >5 files or require architecture decisions.
Specialized debugging agent. Use when facing hard bugs, test failures, or runtime errors that need systematic investigation.
Coordinate multiple Claude Code sessions as a team — lead + teammates with shared task lists, mailbox messaging, and file-lock claiming. Patterns for team sizing, task decomposition, and when to use teams vs sub-agents vs worktrees.
Provider-agnostic multi-LLM deliberation. Three phases — independent responses, cross-model anonymized ranking, chairman synthesis. Provider config from env (OPENAI/ANTHROPIC/FIREWORKS/OPENROUTER/custom OpenAI-compatible base URL). Persists transcript to a wiki page when --wiki <slug> is passed. Use when the user wants multiple AI perspectives, consensus-building, or the "LLM Council" approach for high-stakes reviews, plan critique, or contested learning rules.
LLM-powered quality verification using prompt hooks. Validates commit messages, code patterns, and conventions using AI before allowing operations. Use to set up intelligent guardrails.
Compile a structured literature survey on any AI/ML topic. Agent curates a research bundle (taxonomy + sections + bibliography of real papers) from a public anchor resource, then a chosen LLM generates the survey artifact. Output target is a wiki page (markdown), not a one-off HTML — survey lands in `<wiki>/derived/surveys/<slug>.md` with full bibliography rows in `sources.md`. Provider-agnostic (Anthropic/OpenAI/OpenRouter/Fireworks/custom OpenAI-compat). Use when the user asks for a "survey", "literature review", "lit review", or "deep dive" on a technical topic.
Score every decision point with a Thoroughness Rating (1-10). AI makes the marginal cost of doing things properly near-zero — pick the higher-rated option every time. Includes scope checks to distinguish contained vs unbounded work.
Matches all tools
Hooks run on every tool call, not just specific ones
Executes bash commands
Hook triggers when Bash tool is used
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Modifies files
Hook triggers on file write and edit operations
Modifies files
Hook triggers on file write and edit operations
Uses power tools
Uses Bash, Write, or Edit tools
Uses power tools
Uses Bash, Write, or Edit tools
Self-correcting memory + persistent FTS5-indexed wikis + auto-research loop, all on one SQLite store.
Correct Claude once — it never repeats the mistake. Build a wiki on a topic — it grows itself overnight.
34 skills • 8 agents • 22 commands • 37 hook scripts across 24 events
Works with Claude Code, Cursor, and 32+ agents via SkillKit.
You correct Claude the same way 50 times. You explain conventions every new session. Context compacts, learnings vanish, mistakes repeat. You research the same topic in three different sessions because there is nowhere durable for the answers to land.
Every Claude Code user hits this wall.
Pro Workflow puts a single SQLite store underneath every session.
After 50 sessions you barely correct anything. After a week of auto-research, your wiki on a topic is denser than the curated lists you started from.
Session 1: You → "Don't mock the database in tests"
Claude → Proposes rule → You approve → Saved to SQLite
Session 2: SessionStart loads all learnings + lists your wikis
UserPromptSubmit auto-injects top wiki hits when relevant
Claude writes integration tests, cites the right wiki page
Session 50: Correction rate near zero. Wiki has 200 cited claims.
Pro Workflow is published in two places: the Claude Code plugin marketplace (native), and SkillKit (cross-agent translator). Other agents do not have first-class plugins yet — SkillKit translates the skill bundle into each agent's native skill format.
/plugin marketplace add rohitg00/pro-workflow
/plugin install pro-workflow@pro-workflow
SkillKit translates the 34 skills + 22 commands into each agent's native skill format and drops them in the right config directory.
npx skillkit install rohitg00/pro-workflow --agent <name> --force
Notes:
rohitg00/pro-workflow (the GitHub form), not the bare name — skillkit install resolves providers from owner/repo, not marketplace slugs.--force is currently required: SkillKit's security scanner has open false positives on standard Node patterns (child_process imports, Bearer ${env} template literals) that block legit skills like survey-generator and safe-mode. Tracked at skillkit#129.Supported <name> values: cursor, codex, gemini-cli, opencode, github-copilot, droid (factory), antigravity, amp, clawdbot, cline, codebuddy, commandcode, continue, crush, goose, kilo, kiro-cli, mcpjam, mux, neovate, openhands, pi, qoder, qwen, roo, trae, universal, vercel, windsurf, zencoder. Pass --agent universal for a portable bundle.
After install, run skillkit sync to register the skills with the target agent's config.
If neither path works for your setup, clone and copy the bundle directly. Adjust the destination to your agent's skill directory (e.g. ~/.cursor/rules/, ~/.gemini/extensions/, etc.).
npx claudepluginhub glowelephant/pro-workflowHarness-native ECC operator layer - 60 agents, 232 skills, 75 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
A growing collection of Claude-compatible academic workflow bundles. Covers scientific figures, manuscript writing and polishing, reviewer assessment, citation retrieval, data availability, paper reading, literature search, response letters, paper-to-PPTX conversion, and evidence-grounded Chinese invention patent drafting. Rules are organized as reusable skill folders with explicit workflows and quality checks.
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
Core skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques