Your Claude Code gets smarter every session.

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.

The Problem

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.

The Solution

Pro Workflow puts a single SQLite store underneath every session.

• Self-correction memory — every correction becomes a rule, FTS5-searchable, auto-loaded on session start.
• Knowledge plane — persistent research wikis on disk + FTS5 shadow index, queryable from any session, optionally grown by an auto-research loop.
• Quality gates — LLM-powered hooks, deterministic git/secret guards, compaction-aware state, cost tracking.

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.

Install

/plugin marketplace add rohitg00/pro-workflow
/plugin install pro-workflow@pro-workflow

# Cursor
/add-plugin pro-workflow

# Any agent via SkillKit
npx skillkit install pro-workflow

# Manual
git clone https://github.com/rohitg00/pro-workflow.git /tmp/pw
cp -r /tmp/pw/templates/split-claude-md/* ./.claude/

# Build SQLite-backed components
cd ~/.claude/plugins/*/pro-workflow && npm install && npm run build

60-second tour

# 1. Self-correction (existing)
/learn-rule          # capture a correction
/wrap-up             # end session, persist learnings, audit changes
/insights            # heatmaps, trends, productivity

# 2. Knowledge plane (v3.3, new)
/wiki init agent-memory --title "Agent Memory" --flavor research
/wiki page agent-memory wiki/concepts/episodic-memory.md --type concept
/wiki ask "what is episodic memory" --wiki agent-memory

# 3. Auto-research (budget-capped, opt-in)
/wiki seed agent-memory "memory consolidation in agents"
/wiki research agent-memory --max-pages 5 --budget-usd 0.50

# 4. Hybrid retrieval (BM25 + vector RRF, optional)
/wiki embed agent-memory                       # OPENAI_API_KEY or VOYAGE_API_KEY
/wiki hybrid "consolidation patterns" --wiki agent-memory

# 5. Multi-LLM deliberation (transcript persists as a wiki page)
/wiki council "should we adopt episodic memory?" --wiki agent-memory

# 6. Browse the wiki visually (single-file HTML, S3-shareable)
/wiki view agent-memory
open ~/.pro-workflow/wikis/agent-memory/derived/viewer.html

# Kill switch for any auto loop
touch ~/.pro-workflow/STOP

UserPromptSubmit auto-loads top-3 wiki hits when prompts mention indexed topics. SessionStart lists registered wikis and recent learnings.

What's new in v3.3

Persistent knowledge plane on top of self-correction memory.

Plus: /wiki command (now with view), learn-rule Wiki: <slug> scoping, schema additions (wikis, wiki_pages + FTS5, wiki_sources, wiki_claims, wiki_seeds, wiki_embeddings, learnings_wiki), reactive file-watcher seed enqueue, cron-tick driver, /doctor extended with KB + provider sections.

Comparison

What's inside

34 skills

Knowledge plane (new in v3.3)

Quality gates and observability

Memory and learning

Orchestration and engineering loop

8 agents

22 commands

37 hook scripts across 24 events

SessionStart, SessionEnd, UserPromptSubmit, PreToolUse, PostToolUse, Stop, PreCompact, PostCompact, SubagentStart, SubagentStop, TaskCreated, TaskCompleted, PermissionRequest, PermissionDenied, PostToolUseFailure, TeammateIdle, StopFailure, FileChanged, ConfigChange, Notification, Setup, WorktreeCreate, WorktreeRemove, CwdChanged.

Selected high-leverage hooks:

9 reference guides

How it works

/develop flow

Research before planning. Plan before implementing. Review before committing. Validation gates between every phase.

Architecture

Command → Agent → Skill, layered over a single SQLite store. The knowledge plane (v3.3) plugs into the same store as the learning rules.

Storage

~/.pro-workflow/
├── data.db                 # learnings, sessions, wikis (registry), wiki_pages (+FTS5),
│                           # wiki_sources, wiki_claims, wiki_seeds, wiki_embeddings,
│                           # learnings_wiki
├── wikis/<slug>/           # global-scope wikis (default location)
├── council/<session-id>/   # llm-council transcripts
├── fetchers/               # user-supplied custom source fetchers
├── tick.log                # cron-driven research-tick log
└── STOP                    # touch this file to halt every research loop

Project-scope wikis live at <project>/.claude/wikis/<slug>/ and are committable.

Patterns

Cross-agent support

Works across 32+ AI coding agents via SkillKit:

npx skillkit install pro-workflow
npx skillkit translate pro-workflow --agent cursor
npx skillkit translate pro-workflow --agent codex
npx skillkit translate pro-workflow --agent gemini-cli

Supported: Claude Code, Cursor, Codex CLI, Gemini CLI, Windsurf, OpenCode, Kiro, Amp, Goose, Roo, and 27 more.

Configuration

Settings

See settings.example.json for production-ready configuration: permission rules, output style, auto-compaction, custom spinner verbs.

MCP

See mcp-config.example.json:

• context7 — live documentation lookup
• playwright — browser automation (most token-efficient)
• GitHub — PRs, issues, code search

Rule: start with three MCPs, add only for concrete needs.

Knowledge plane env

Structure

pro-workflow/
├── skills/           # 34 skills
├── agents/           # 8 agents
├── commands/         # 22 slash commands
├── scripts/          # 37 hook scripts (24 events)
├── docs/             # 9 reference guides + index.html + infographic.html
├── rules/            # rule packs (Cursor + universal)
├── contexts/         # context modes
├── templates/        # split CLAUDE.md + AGENTS.md
├── src/              # TypeScript source (SQLite + embeddings)
└── config.json

Tips from the community

"80% of my code is written by AI, 20% is spent reviewing and correcting it." — Andrej Karpathy

"Use subagents to throw more compute at a problem — offload tasks to keep your main context clean." — Boris Cherny

"If you do something more than once a day, turn it into a skill or command." — Boris Cherny

"Write detailed specs and reduce ambiguity before handing work off." — Boris Cherny

"Skill description field is a trigger, not a summary — write it for the model." — Thariq Shihipar

Philosophy

1. Compound improvements — small corrections lead to big gains.
2. Trust but verify — let AI work, review at checkpoints.
3. Zero dead time — parallel sessions keep momentum.
4. Memory is precious — both yours and Claude's.
5. Persistent over ephemeral — if you'll need it next session, write it down on disk.
6. Orchestrate, don't micromanage — wire patterns together, let agents execute.

Related projects

Star history

If pro-workflow saves you time, star the repo so others can find it.



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