Agent skill

Parallel Dev Cycle

by catlog22 in catlog22/Claude-Code-Workflow

Multi-agent parallel development cycle with requirement analysis, exploration planning, code development, and validation.

MITAuto-check: notesAgent Workflows

Install Parallel Dev Cycle

skills CLI
$ npx skills add catlog22/Claude-Code-Workflow --skill parallel-dev-cycle -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install catlog22/Claude-Code-Workflow parallel-dev-cycle --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/catlog22/Claude-Code-Workflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.codex/skills/parallel-dev-cycle .claude/skills/parallel-dev-cycle && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
parallel-dev-cycle
GitHub stars
2.1k
Token cost
~4.3k tokens
SKILL.md length
962 words
Files
10
Skills in repo
82
Repo updated
First seen
Licence
MIT

At a glance

Multi-agent parallel development cycle with requirement analysis, exploration planning, code development, and validation.

  • Works in 4 steps: Requirements Analysis & Extension (RA) -… → Exploration & Planning (EP) - Codebase… → Code Development (CD) - Code development… → …
  • Parallel-dev-cycle
  • SKILL.md covers Architecture Overview, Key Design Principles, Arguments and Auto Mode, plus 13 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Parallel Dev Cycle is an agent skill from catlog22/Claude-Code-Workflow. Multi-agent parallel development cycle with requirement analysis, exploration planning, code development, and validation. Orchestration runs inline in main flow (no separate orchestrator agent). Supports continuous iteration with markdown progress documentation. Triggers on "parallel-dev-cycle".

Its SKILL.md is about 4.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files (for example `phases/00-prep-checklist.md`, `phases/01-session-init.md` and `phases/02-agent-execution.md`).

It sits in Agent Workflows, covering Multi-agent orchestration. The repository describes itself as: JSON-driven multi-agent cadence-team development framework with intelligent CLI orchestration (Gemini/Qwen/Codex), context-first architecture, and automated workflow execution. The licence is MIT.

When your agent uses it

  • Parallel-dev-cycle
  • Tasks that involve Multi-agent orchestration

Example prompts

  • “parallel-dev-cycle”
  • “/parallel-dev-cycle”

Requirements

  • Pre-approved tools (allowed-tools): spawn_agent, wait_agent, send_message, followup_task, close_agent, request_user_input, Read, Write, Edit, Bash, Glob, Grep

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Requirements Analysis & Extension (RA) - Requirement analysis and self-enhancement
  2. Exploration & Planning (EP) - Codebase exploration and implementation planning
  3. Code Development (CD) - Code development with debug strategy support
  4. Validation & Archival Summary (VAS) - Validation and archival summary

What it can do on your machine

Read from SKILL.md and the folder at commit 07491b0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • spawn_agent
    • wait_agent
    • send_message
    • followup_task
    • close_agent
    • request_user_input
    • Read
    • Write
    • Edit
    • Bash

    …and 2 more on the same allowed-tools line.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are javascript, json, jsonl and bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Parallel Dev Cycle loads about 4.3k tokens when it runs. Until then it costs about 79 tokens; SKILL.md has 962 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~79
When it runs · the whole SKILL.md, loaded when a task matches
~4.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: spawn_agent, wait_agent, send_message, followup_task, close_agent, request_user_input, Read, Write, 

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from catlog22/Claude-Code-Workflow at commit 07491b0, republished under its MIT licence (© catlog22). 962 words, ~4,339 tokens.

Download SKILL.mdSave it as .claude/skills/parallel-dev-cycle/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
name
parallel-dev-cycle
description
Multi-agent parallel development cycle with requirement analysis, exploration planning, code development, and validation. Orchestration runs inline in main flow (no separate orchestrator agent). Supports continuous iteration with markdown progress documentation. Triggers on "parallel-dev-cycle".
allowed-tools
spawn_agent, wait_agent, send_message, followup_task, close_agent, request_user_input, Read, Write, Edit, Bash, Glob, Grep

Parallel Dev Cycle

Multi-agent parallel development cycle using Codex subagent pattern with four specialized workers:

  1. Requirements Analysis & Extension (RA) - Requirement analysis and self-enhancement
  2. Exploration & Planning (EP) - Codebase exploration and implementation planning
  3. Code Development (CD) - Code development with debug strategy support
  4. Validation & Archival Summary (VAS) - Validation and archival summary

Orchestration logic (phase management, state updates, feedback coordination) runs inline in the main flow — no separate orchestrator agent is spawned. Only 4 worker agents are allocated.

Each agent maintains one main document (e.g., requirements.md, plan.json, implementation.md) that is completely rewritten per iteration, plus auxiliary logs (changes.log, debug-log.ndjson) that are append-only.

Architecture Overview

┌─────────────────────────────────────────────────────────────┐
│                    User Input (Task)                        │
└────────────────────────────┬────────────────────────────────┘
                             │
                             v
              ┌──────────────────────────────┐
              │  Main Flow (Inline Orchestration)  │
              │  Phase 1 → 2 → 3 → 4              │
              └──────────────────────────────┘
                             │
        ┌────────────────────┼────────────────────┐
        │                    │                    │
        v                    v                    v
    ┌────────┐         ┌────────┐         ┌────────┐
    │  RA    │         │  EP    │         │  CD    │
    │Agent   │         │Agent   │         │Agent   │
    └────────┘         └────────┘         └────────┘
        │                    │                    │
        └────────────────────┼────────────────────┘
                             │
                             v
                         ┌────────┐
                         │  VAS   │
                         │ Agent  │
                         └────────┘
                             │
                             v
              ┌──────────────────────────────┐
              │    Summary Report            │
              │  & Markdown Docs             │
              └──────────────────────────────┘

Key Design Principles

  1. Main Document + Auxiliary Logs: Each agent maintains one main document (rewritten per iteration) and auxiliary logs (append-only)
  2. Version-Based Overwrite: Main documents completely rewritten per version; logs append-only
  3. Automatic Archival: Old main document versions automatically archived to history/ directory
  4. Complete Audit Trail: Changes.log (NDJSON) preserves all change history
  5. Parallel Coordination: Four agents launched simultaneously; coordination via shared state and inline main flow
  6. File References: Use short file paths instead of content passing
  7. Self-Enhancement: RA agent proactively extends requirements based on context
  8. Shared Discovery Board: All agents share exploration findings via discoveries.ndjson — read on start, write as you discover, eliminating redundant codebase exploration

Arguments

ArgRequiredDescription
TASKOne of TASK or --cycle-idTask description (for new cycle, mutually exclusive with --cycle-id)
--cycle-idOne of TASK or --cycle-idExisting cycle ID to continue (from API or previous session)
--extendNoExtension description (only valid with --cycle-id)
--autoNoAuto-cycle mode (run all phases sequentially without user confirmation)
--parallelNoNumber of parallel agents (default: 4, max: 4)

Auto Mode

When --auto: Run all phases sequentially without user confirmation between iterations. Use recommended defaults for all decisions. Automatically continue iteration loop until tests pass or max iterations reached.

Prep Package Integration

When prep-package.json exists at {projectRoot}/.workflow/.cycle/prep-package.json, Phase 1 consumes it to:

  • Use refined task description instead of raw TASK
  • Apply auto-iteration config (convergence criteria, phase gates)
  • Inject per-iteration agent focus directives (0→1 vs 1→100)

Prep packages are generated by the interactive prompt /prompts:prep-cycle. See phases/00-prep-checklist.md for schema.

Execution Flow

Input Parsing:
   └─ Parse arguments (TASK | --cycle-id + --extend)
   └─ Convert to structured context (cycleId, state, progressDir)
   └─ Initialize progress tracking: functions.update_plan([...phases])

Phase 1: Session Initialization
   └─ Ref: phases/01-session-init.md
      ├─ Create new cycle OR resume existing cycle
      ├─ Initialize state file and directory structure
      └─ Output: cycleId, state, progressDir

Phase 2: Agent Execution (Parallel)
   └─ Ref: phases/02-agent-execution.md
      ├─ Tasks attached: Spawn RA → Spawn EP → Spawn CD → Spawn VAS → Wait all
      ├─ Spawn RA, EP, CD, VAS agents in parallel
      ├─ Wait for all agents with timeout handling
      └─ Output: agentOutputs (4 agent results)

Phase 3: Result Aggregation & Iteration
   └─ Ref: phases/03-result-aggregation.md
      ├─ Parse PHASE_RESULT from each agent
      ├─ Detect issues (test failures, blockers)
      ├─ Decision: Issues found AND iteration < max?
      │   ├─ Yes → Send feedback via followup_task, loop back to Phase 2
      │   └─ No → Proceed to Phase 4
      └─ Output: parsedResults, iteration status

Phase 4: Completion & Summary
   └─ Ref: phases/04-completion-summary.md
      ├─ Generate unified summary report
      ├─ Update final state
      ├─ Sync session state: $session-sync -y "Dev cycle complete: {iterations} iterations"
      ├─ Close all agents
      └─ Output: final cycle report with continuation instructions

Phase Reference Documents (read on-demand when phase executes):

PhaseDocumentPurpose
1phases/01-session-init.mdSession creation/resume and state initialization
2phases/02-agent-execution.mdParallel agent spawning and execution
3phases/03-result-aggregation.mdResult parsing, feedback generation, iteration handling
4phases/04-completion-summary.mdFinal summary generation and cleanup

Data Flow

User Input (TASK | --cycle-id + --extend)
    ↓
[Parse Arguments]
    ↓ cycleId, state, progressDir

Phase 1: Session Initialization
    ↓ cycleId, state, progressDir (initialized/resumed)

Phase 2: Agent Execution
    ├─ All agents read coordination/discoveries.ndjson on start
    ├─ Each agent explores → writes new discoveries to board
    ├─ Later-finishing agents benefit from earlier agents' findings
    ↓ agentOutputs {ra, ep, cd, vas} + shared discoveries.ndjson

Phase 3: Result Aggregation
    ↓ parsedResults, hasIssues, iteration count
    ↓ [Loop back to Phase 2 if issues and iteration < max]
    ↓ (discoveries.ndjson carries over across iterations)

Phase 4: Completion & Summary
    ↓ finalState, summaryReport

Return: cycle_id, iterations, final_state

Session Structure

{projectRoot}/.workflow/.cycle/
├── {cycleId}.json                                 # Master state file
├── {cycleId}.progress/
    ├── ra/
    │   ├── requirements.md                        # Current version (complete rewrite)
    │   ├── changes.log                            # NDJSON complete history (append-only)
    │   └── history/                               # Archived snapshots
    ├── ep/
    │   ├── exploration.md                         # Codebase exploration report
    │   ├── architecture.md                        # Architecture design
    │   ├── plan.json                              # Structured task list (current version)
    │   ├── changes.log                            # NDJSON complete history
    │   └── history/
    ├── cd/
    │   ├── implementation.md                      # Current version
    │   ├── debug-log.ndjson                       # Debug hypothesis tracking
    │   ├── changes.log                            # NDJSON complete history
    │   └── history/
    ├── vas/
    │   ├── summary.md                             # Current version
    │   ├── changes.log                            # NDJSON complete history
    │   └── history/
    └── coordination/
        ├── discoveries.ndjson                     # Shared discovery board (all agents append)
        ├── timeline.md                            # Execution timeline
        └── decisions.log                          # Decision log

State Management

Master state file: {projectRoot}/.workflow/.cycle/{cycleId}.json

json
{
  "cycle_id": "cycle-v1-20260122T100000-abc123",
  "title": "Task title",
  "description": "Full task description",
  "status": "created | running | paused | completed | failed",
  "created_at": "ISO8601", "updated_at": "ISO8601",
  "max_iterations": 5, "current_iteration": 0,
  "agents": {
    "ra":  { "status": "idle | running | completed | failed", "output_files": [] },
    "ep":  { "status": "idle", "output_files": [] },
    "cd":  { "status": "idle", "output_files": [] },
    "vas": { "status": "idle", "output_files": [] }
  },
  "current_phase": "init | ra | ep | cd | vas | aggregation | complete",
  "completed_phases": [],
  "requirements": null, "plan": null, "changes": [], "test_results": null,
  "coordination": { "feedback_log": [], "blockers": [] }
}

Recovery: If state corrupted, rebuild from .progress/ markdown files and changes.log.

Progress Tracking

Initialization (MANDATORY)
javascript
// Initialize progress tracking after input parsing
functions.update_plan([
  { id: "phase-1", title: "Phase 1: Session Initialization", status: "in_progress" },
  { id: "phase-2", title: "Phase 2: Agent Execution", status: "pending" },
  { id: "phase-3", title: "Phase 3: Result Aggregation", status: "pending" },
  { id: "phase-4", title: "Phase 4: Completion & Summary", status: "pending" }
])
Phase Transitions
javascript
// After Phase 1 completes
functions.update_plan([
  { id: "phase-1", status: "completed" },
  { id: "phase-2", status: "in_progress" }
])

// After Phase 2 completes
functions.update_plan([
  { id: "phase-2", status: "completed" },
  { id: "phase-3", status: "in_progress" }
])

// After Phase 3 — iterate or complete
// If iterating back to Phase 2:
functions.update_plan([
  { id: "phase-3", status: "completed" },
  { id: "phase-2", title: "Phase 2: Agent Execution (Iteration N)", status: "in_progress" }
])
// If proceeding to Phase 4:
functions.update_plan([
  { id: "phase-3", status: "completed" },
  { id: "phase-4", status: "in_progress" }
])

// After Phase 4 completes
functions.update_plan([{ id: "phase-4", status: "completed" }])

Versioning

  • 1.0.0: Initial cycle → 1.x.0: Each iteration (minor bump)
  • Each iteration: archive old → complete rewrite → append changes.log
Archive: copy requirements.md → history/requirements-v1.0.0.md
Rewrite: overwrite requirements.md with v1.1.0 (complete new content)
Append:  changes.log ← {"timestamp","version":"1.1.0","action":"update","description":"..."}
Agent OutputRewrite (per iteration)Append-only
RArequirements.mdchanges.log
EPexploration.md, architecture.md, plan.jsonchanges.log
CDimplementation.md, issues.mdchanges.log, debug-log.ndjson
VASsummary.md, test-results.jsonchanges.log

Coordination Protocol

Execution Order: RA → EP → CD → VAS (dependency chain, all spawned in parallel but block on dependencies)

Show full SKILL.md (476 more words)Show less
Shared Discovery Board

All agents share a real-time discovery board at coordination/discoveries.ndjson. Each agent reads it on start and appends findings during work. This eliminates redundant codebase exploration.

Lifecycle:

  • Created by the first agent to write a discovery (file may not exist initially)
  • Carries over across iterations — never cleared or recreated
  • Agents use Bash echo '...' >> discoveries.ndjson to append entries

Format: NDJSON, each line is a self-contained JSON with required top-level fields ts, agent, type, data:

jsonl
{"ts":"2026-01-22T10:00:00+08:00","agent":"ra","type":"tech_stack","data":{"language":"TypeScript","framework":"Express","test":"Jest","build":"tsup"}}

Discovery Types:

typeDedup KeyWritersReadersRequired data Fields
tech_stacksingletonRAEP, CD, VASlanguage, framework, test, build
project_configdata.pathRAEP, CDpath, key_deps[], scripts{}
existing_featuredata.nameRA, EPCDname, files[], summary
architecturesingletonEPCD, VASpattern, layers[], entry
code_patterndata.nameEP, CDCD, VASname, description, example_file
integration_pointdata.fileEPCDfile, description, exports[]
similar_impldata.featureEPCDfeature, files[], relevance
code_conventionsingletonCDVASnaming, imports, formatting
utilitydata.nameCDVASname, file, usage
test_commandsingletonCD, VASVAS, CDunit, integration(opt), coverage(opt)
test_baselinesingletonVASCDtotal, passing, coverage_pct, framework, config
test_patternsingletonVASCDstyle, naming, fixtures
blockerdata.issueanyallissue, severity, impact

Protocol Rules:

  1. Read board before own exploration → skip covered areas (if file doesn't exist, skip)
  2. Write discoveries immediately via Bash echo >> → don't batch
  3. Deduplicate — check existing entries; skip if same type + dedup key value already exists
  4. Append-only — never modify or delete existing lines
Agent → Main Flow Communication
PHASE_RESULT:
- phase: ra | ep | cd | vas
- status: success | failed | partial
- files_written: [list]
- summary: one-line summary
- issues: []
Main Flow → Agent Communication

Feedback via followup_task (file refs + issue summary, never full content):

## FEEDBACK FROM [Source]
[Issue summary with file:line references]
## Reference
- File: .progress/vas/test-results.json (v1.0.0)
## Actions Required
1. [Specific fix]

Rules: Only main flow writes state file. Agents read state, write to own .progress/{agent}/ directory only.

Core Rules

  1. Start Immediately: First action is functions.update_plan initialization, then Phase 1 execution
  2. Progressive Phase Loading: Read phase docs ONLY when that phase is about to execute
  3. Parse Every Output: Extract PHASE_RESULT data from each agent for next phase
  4. Auto-Continue: After each phase, execute next pending phase automatically
  5. Track Progress: Update functions.update_plan at each phase transition
  6. Single Writer: Only main flow writes to master state file; agents report via PHASE_RESULT
  7. File References: Pass file paths between agents, not content
  8. DO NOT STOP: Continuous execution until all phases complete or max iterations reached

Error Handling

Error TypeRecovery
Agent timeoutfollowup_task requesting convergence, then retry
State corruptedRebuild from progress markdown files and changes.log
Agent failedRe-spawn agent with previous context
Conflicting resultsMain flow sends reconciliation request
Missing filesRA/EP agents identify and request clarification
Max iterations reachedGenerate summary with remaining issues documented

Coordinator Checklist (Main Flow)

Before Each Phase
  • Read phase reference document
  • Check current state for dependencies
  • Update functions.update_plan with phase status
After Each Phase
  • Parse agent outputs (PHASE_RESULT)
  • Update master state file
  • Update functions.update_plan phase completion
  • Determine next action (continue / iterate / complete)

Reference Documents

DocumentPurpose
roles/Agent role definitions (RA, EP, CD, VAS)

Usage

bash
# Start new cycle
/parallel-dev-cycle TASK="Implement real-time notifications"

# Continue cycle
/parallel-dev-cycle --cycle-id=cycle-v1-20260122-abc123

# Iteration with extension
/parallel-dev-cycle --cycle-id=cycle-v1-20260122-abc123 --extend="Also add email notifications"

# Auto mode
/parallel-dev-cycle --auto TASK="Add OAuth authentication"

© catlog22, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 9 other files in .codex/skills/parallel-dev-cycle of catlog22/Claude-Code-Workflow.

  • SKILL.md
  • phases/00-prep-checklist.md
  • phases/01-session-init.md
  • phases/02-agent-execution.md
  • phases/03-result-aggregation.md
  • phases/04-completion-summary.md
  • roles/code-developer.md
  • roles/exploration-planner.md
  • roles/requirements-analyst.md
  • roles/validation-archivist.md

Open the folder on GitHubat commit 07491b0

Compare with similar skills

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Categories

Questions about Parallel Dev Cycle

What does Parallel Dev Cycle do?

Multi-agent parallel development cycle with requirement analysis, exploration planning, code development, and validation. Parallel Dev Cycle is an agent skill from catlog22/Claude-Code-Workflow. Multi-agent parallel development cycle with requirement analysis, exploration planning, code development, and validation.

When should I use Parallel Dev Cycle?

Parallel Dev Cycle fits situations like: parallel-dev-cycle; tasks that involve Multi-agent orchestration.

How do I install Parallel Dev Cycle in Claude Code?

Run `npx skills add catlog22/Claude-Code-Workflow --skill parallel-dev-cycle -a claude-code`. Or copy the skill folder (.codex/skills/parallel-dev-cycle in catlog22/Claude-Code-Workflow) into .claude/skills/parallel-dev-cycle in your project. Claude Code loads it when a task matches its description.

How do I install Parallel Dev Cycle in Codex?

Run `npx skills add catlog22/Claude-Code-Workflow --skill parallel-dev-cycle -a codex`. Or copy the skill folder (.codex/skills/parallel-dev-cycle in catlog22/Claude-Code-Workflow) into .agents/skills/parallel-dev-cycle in your project. Codex loads it when a task matches its description.

Can I use Parallel Dev Cycle in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add catlog22/Claude-Code-Workflow --skill parallel-dev-cycle -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/parallel-dev-cycle, .gemini/skills/parallel-dev-cycle, .github/skills/parallel-dev-cycle and .opencode/skills/parallel-dev-cycle in your project.

What does Parallel Dev Cycle need to run?

SKILL.md names no scripts, command-line tools or credentials: Parallel Dev Cycle is instructions for the agent only. Its frontmatter pre-approves these tools: spawn_agent, wait_agent, send_message, followup_task, close_agent, request_user_input, Read, Write, Edit, Bash, Glob, Grep.

Does Parallel Dev Cycle access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Parallel Dev Cycle safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Parallel Dev Cycle use?

Parallel Dev Cycle is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Parallel Dev Cycle use?

About 4.3k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Parallel Dev Cycle?

Skills that share tags, products or a category with Parallel Dev Cycle: Orca CLI (stablyai/orca, 87k stars), Paseo Advisor Second Opinion (getpaseo/paseo, 20k stars), O2 Review Loop (openobserve/openobserve, 22k stars) and Paseo Committee (getpaseo/paseo, 20k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Parallel Dev Cycle?

catlog22 (a GitHub user) maintains it in catlog22/Claude-Code-Workflow, which has 2,130 GitHub stars. The repository holds 82 skills in this directory. The repository was last updated on June 18, 2026.

Source: catlog22/Claude-Code-Workflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.