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Pro Workflow

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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 skills8 agents22 commands37 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.

Self-Correction Loop

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
Other install methods
# 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.

Skill Purpose
wiki-builder Persistent FTS5-indexed research wikis. 9 flavors: research, paper, domain, product, person, organization, project, codebase, incident. Path-traversal-guarded.
wiki-query BM25 retrieval with snippets. ask, related, show. Auto-injects on UserPromptSubmit.
wiki-research-loop Budget-capped BFS. Pluggable source fetchers (web/arXiv/GitHub + custom). Convergence detection, kill-switch, atomic seed claim, try/finally state guards.
llm-council Provider-agnostic 3-phase deliberation (Anthropic/OpenAI/OpenRouter/Fireworks/custom). Promise.allSettled so one provider failure doesn't abort the run. Transcript persists as a wiki page.
survey-generator Provider-agnostic literature survey. Output target = wiki markdown page. Bibliography validation (uniqueness + section-paper refs), citation IDs aligned with sources.md rows.
wiki-viewer Single-file HTML viewer for any wiki: pages + sources + seeds + link graph + in-browser search + "copy as seed" CTAs. S3-shareable. Applied lessons from Thariq Shihipar's HTML-as-output thesis.

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

Feature Pro Workflow Superpowers ECC gstack GSD
Self-correcting memory (SQLite + FTS5) Yes No No No No
Persistent research wikis (FTS5) Yes No No No No
Auto-research loop (budget-capped BFS) Yes No No No No
Hybrid retrieval (BM25 + vector + RRF) Yes No No No No
Multi-provider LLM council Yes No No No No
LLM-powered hooks (type: "prompt") Yes No No No No
Permission denial analysis Yes No No No No
Compaction-aware state preservation Yes No No No No
Cost tracking and budget alerts Yes No No No No
MCP overhead auditing Yes No No No No
Cross-agent (32+ agents via SkillKit) Yes No Some No No
Skills 34 14 140+ 18+ 0
Agents 8 5 36 0 18
Commands 22 3 60+ 5+ 57
Hook events 24 8 18 0 0

What's inside

34 skills

Knowledge plane (new in v3.3)

Skill What it does
wiki-builder Scaffold + register FTS5-indexed research wikis
wiki-query BM25 retrieval, snippets, related, show
wiki-research-loop Budget-capped BFS over web/arXiv/GitHub fetchers
llm-council Provider-agnostic 3-phase multi-LLM deliberation
survey-generator Literature survey artifact, output to a wiki page
wiki-viewer Single-file HTML viewer (pages, sources, seeds, link graph, search)

Quality gates and observability

Skill What it does
smart-commit Quality gates, staged review, conventional commits
llm-gate AI-powered commit and secret hooks (type: "prompt")
permission-tuner Analyze denials, generate allow/deny rules
compact-guard State preservation through compaction cycles
cost-tracker Session cost awareness with budget benchmarks
mcp-audit MCP server token-overhead analysis
token-efficiency Anti-sycophancy + tool-call budgets + read-before-write
safe-mode Guardrails for destructive operations
insights Session analytics, correction trends, productivity
thoroughness-scoring Rate completeness of implementations
deslop Remove AI-generated code slop from a diff

Memory and learning

Skill What it does
pro-workflow Core 8 patterns
learn-rule Capture corrections (now wiki-scopeable)
replay-learnings Surface past learnings for the current task
wrap-up End-of-session ritual
session-handoff Resume documents for the next session

Orchestration and engineering loop

Skill What it does
orchestrate Multi-phase Research → Plan → Implement → Review
agent-teams Multi-instance coordination, shared task list
batch-orchestration Parallel worktree agents for large changes
parallel-worktrees Git worktree setup for zero dead time
context-engineering Write/Select/Compress/Isolate framework
context-optimizer Token management, context budget, MCP audit
auto-setup Auto-detect project type, configure quality gates
file-watcher Reactive workflows on config and dependency changes
bug-capture Capture defects as durable issues without leaking paths
module-map One-screen map of an unfamiliar codebase area
plan-interrogate Stress-test a plan by walking its decision tree
sprint-status Track multi-session progress

8 agents

Agent Purpose
planner Break down complex tasks (read-only, approval-gated)
reviewer Code review and security audit (checklist-based)
scout Confidence-gated exploration (background, worktree-isolated)
orchestrator Multi-phase feature development
debugger Systematic, hypothesis-driven bug investigation
context-engineer Context-window analysis (lightweight, read-only)
permission-analyst Denial-pattern analysis, rule-optimization recommendations
cost-analyst Token-usage analysis, identify expensive operations

22 commands

Command What it does
/wiki Knowledge-plane entry: init, page, ask, hybrid, seed, research, council, survey, embed, status
/develop Multi-phase feature build with validation gates
/commit Smart commit with quality gates
/wrap-up End-of-session checklist and learning capture
/learn-rule / /learn Extract correction or learn Claude Code best practices
/doctor Setup health check (now includes wiki KB + council providers)
/insights Session analytics and correction heatmap
/replay Surface past learnings for the current task
/handoff Session handoff document
/search / /list Search and list stored learnings
/deslop Remove AI-generated code slop
/context-optimizer Audit and optimize context-window usage
/parallel Set up git worktrees for parallel sessions
/safe-mode Toggle destructive-operation guardrails
/sprint-status Track multi-session progress
/auto-setup Auto-detect project type, configure quality gates
/compact-guard Protected compaction with state preservation
/cost-tracker Track session costs and optimization tips
/mcp-audit Audit MCP servers for token overhead
/permission-tuner Generate allow/deny rules from denial patterns

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:

Hook Script Effect
SessionStart session-start.js Loads learnings; lists registered wikis
UserPromptSubmit prompt-submit.js Auto-injects top-3 wiki hits when prompts match the index
Stop learn-capture.js Auto-captures [LEARN] blocks (now parses Wiki: <slug>)
FileChanged file-changed.js Edits inside a wiki tree enqueue verify-seeds
PreToolUse(Bash) commit-validate.js, git-blast-radius.js, pre-push-check.js Conventional commit + destructive op + push guardrails
PreToolUse(Write) secret-scan.js LLM-powered secret detection
PreCompact / PostCompact pre-compact.js, post-compact.js Save and re-inject critical context summary

9 reference guides

Guide What's covered
settings-guide.md Settings keys, permission modes, hierarchy
cli-cheatsheet.md CLI flags, keyboard shortcuts, slash commands
orchestration-patterns.md Command → Agent → Skill architecture, agent teams
context-engineering.md Write/Select/Compress/Isolate, memory taxonomy, compaction
agent-teams.md Setup, decomposition, teams vs sub-agents
context-loading.md CLAUDE.md loading, agent memory, skills discovery
cross-agent-workflows.md Claude Code + Cursor together, SkillKit translation
decision-framework.md When to use which pattern
daily-habits.md Session habits, debugging tips, anti-patterns

How it works

/develop flow

Development Flow

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

Architecture

Architecture Diagram

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

Pattern What it does
Self-Correction Loop Claude learns from corrections automatically
Knowledge Plane Wiki + auto-research loop on the same SQLite store
Multi-Phase Dev Research → Plan → Implement → Review with gates
Parallel Worktrees Zero dead time with native claude -w
Wrap-Up Ritual End sessions with intention, capture learnings
Split Memory Modular CLAUDE.md for complex projects
80/20 Review Batch reviews at checkpoints
Context Engineering Write/Select/Compress/Isolate for token management
Agent Teams Multi-instance coordination with shared task list
Batch Orchestration Parallel worktree agents for large-scale changes
LLM Gates AI-powered verification before destructive operations
Permission Tuning Denial-pattern analysis to reduce prompt fatigue
Token Efficiency Anti-sycophancy + tool-call budgets + read-before-write
Multi-LLM Council Provider-agnostic 3-phase deliberation for high-stakes calls

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

Env When
WIKI_ROOT Override default ~/.pro-workflow/wikis
OPENAI_API_KEY / VOYAGE_API_KEY Enable hybrid retrieval (embeddings)
ANTHROPIC_API_KEY / OPENAI_API_KEY / OPENROUTER_API_KEY / FIREWORKS_API_KEY / LLM_COUNCIL_BASE_URL+LLM_COUNCIL_API_KEY Pick a council provider (first match wins)
WIKI_LOOP_BUDGET_USD / WIKI_LOOP_MAX_PAGES / WIKI_LOOP_MAX_DEPTH Per-run loop overrides
GH_TOKEN / GITHUB_TOKEN Lifts GitHub-fetcher rate limit

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

Project Description
everything-claude-code 140+ skills, 36 agents — the comprehensive collection
claude-code-best-practice Curated tips, comparisons, community best practices
SkillKit Universal CLI for managing skills across 32+ agents
awesome-claude-code-toolkit 850+ files, 135 agents, 176 plugins — curated directory

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