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Agentic Workflow

  • 545 installs
  • 3.9k repo stars
  • Updated January 26, 2026
  • parcadei/continuous-claude-v3

agentic-workflow is a Claude Code skill that orchestrates a standard multi-agent implementation pipeline with background Task subagents for developers who need continuous momentum across long, multi-step coding sessions.

About

agentic-workflow from parcadei/continuous-claude-v3 defines a standard multi-agent pipeline for implementation tasks in Claude Code. The main conversation stays as pure orchestration while Research, planning, and implementation agents run with run_in_background true via the Task tool, never TaskOutput, to avoid flooding context with full transcripts. Each agent writes outputs to .claude/cache/agents/<stage>/ for injection into subsequent agents, keeping the main thread minimal. Developers reach for agentic-workflow when implementing features that need verified research, staged handoffs, and hours-long sessions without losing context or momentum across agent stages.

  • Enables persistent agentic loops that maintain state and intent across dozens of Claude turns
  • Automatically surfaces next actions, open questions, and decision gates
  • Supports 4 distinct workflow modes: research, implementation, review, and iteration
  • Hard-gate: requires explicit human approval before executing high-impact changes
  • Produces traceable decision log and artifact manifest after each cycle

Agentic Workflow by the numbers

  • 545 all-time installs (skills.sh)
  • +3 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #1,679 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/parcadei/continuous-claude-v3 --skill agentic-workflow

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Listed on Skillselion
Installs545
repo stars3.9k
Last updatedJanuary 26, 2026
Repositoryparcadei/continuous-claude-v3

How do you orchestrate multi-agent coding sessions?

Keep Claude continuously engaged across long, multi-step development sessions without losing context or momentum.

Who is it for?

Developers running long Claude Code implementation sessions who want research, planning, and coding agents coordinated without transcript bloat.

Skip if: Single-prompt quick fixes or teams not using Claude Code Task subagents and background agent execution.

When should I use this skill?

A multi-step implementation needs coordinated research, planning, and coding agents across a long Claude Code session.

What you get

Staged agent cache files under .claude/cache/agents/, background Task runs, and a minimal main-thread orchestration log.

  • Staged agent cache files
  • Background agent run coordination
  • Multi-step implementation pipeline

Files

SKILL.mdMarkdownGitHub ↗

Agentic Workflow Pattern

Standard multi-agent pipeline for implementation tasks.

Architecture Principles

  • Use run_in_background: true for all agents to keep main context minimal
  • Use Task tool (never TaskOutput) to avoid receiving full agent transcripts
  • Agents write outputs to .claude/cache/agents/<stage>/ for injection into subsequent agents
  • Main conversation is pure orchestration — no heavy lifting, only coordination

Workflow Stages

1. Research Agent

Task(subagent_type="oracle", run_in_background=true, prompt="""
Query NIA Oracle (via /nia-docs skill) to verify approach and gather best practices.

Output to: .claude/cache/agents/oracle/<task>-research.md
""")
  • Enforce NIA as the research layer
  • Output: Research findings

2. Planning Agent

Task(subagent_type="plan-agent", run_in_background=true, prompt="""
Read: .claude/cache/agents/oracle/<task>-research.md
Use RP-CLI to analyze the target codebase section.
Generate implementation plan informed by research.

Output to: .claude/cache/agents/plan-agent/<task>-plan.md
""")
  • Receives: Research agent output as context
  • Output: Implementation plan

3. Validation Agent

Task(subagent_type="validate-agent", run_in_background=true, prompt="""
Read: .claude/cache/agents/plan-agent/<task>-plan.md
Read: .claude/cache/agents/oracle/<task>-research.md
Review plan against research findings and best practices.

Output to: .claude/cache/agents/validate-agent/<task>-validated.md
""")
  • Reviews plan against research
  • Output: Validated plan with amendments

4. Implementation Agent

Task(subagent_type="agentica-agent", run_in_background=true, prompt="""
Read: .claude/cache/agents/validate-agent/<task>-validated.md
Read: .claude/cache/agents/oracle/<task>-research.md

TDD approach: Write failing tests FIRST, then implement.
Run tests to verify.

Output summary to: .claude/cache/agents/implement-agent/<task>-implementation.md
""")
  • Receives: Validated plan + research context
  • TDD: Failing tests first
  • Output: Implementation + tests

5. Review Agent

Task(subagent_type="review-agent", run_in_background=true, prompt="""
Read: .claude/cache/agents/implement-agent/<task>-implementation.md
Read: .claude/cache/agents/validate-agent/<task>-validated.md
Read: .claude/cache/agents/oracle/<task>-research.md

Cross-reference implementation against plan and research.
Run tests to confirm passing.

Output to: .claude/cache/agents/review-agent/<task>-review.md
""")
  • Cross-references all artifacts
  • Confirms tests pass
  • Output: Review summary

Agent Progress Monitoring

# Watch for system reminders:
# "Agent a42a16e progress: 6 new tools used, 88914 new tokens"

# Poll for output files:
find .claude/cache/agents -name "*.md" -mmin -5

# Check task file size growth:
wc -c /tmp/claude/.../tasks/<id>.output

Stuck detection: 1. Progress reminders stop arriving 2. Task output file size stops growing 3. Expected output file not created after reasonable time

Directory Structure

.claude/cache/agents/
├── oracle/
│   └── <task>-research.md
├── plan-agent/
│   └── <task>-plan.md
├── validate-agent/
│   └── <task>-validated.md
├── implement-agent/
│   └── <task>-implementation.md
└── review-agent/
    └── <task>-review.md

Key Rules

1. Never use TaskOutput - floods context with 70k+ token transcripts 2. Always run_in_background=true - isolates agent context 3. File-based handoff - each agent reads previous agent's output file 4. Poll, don't block - check file system for outputs, don't wait 5. TDD in implementation - failing tests first, then make them pass

Source

  • Session 2026-01-01: SDK Phase 3 implementation using this pattern

Related skills

How it compares

Choose agentic-workflow when coordinating multiple Claude Code Task subagents across long builds rather than single-shot code generation prompts.

FAQ

Why does agentic-workflow use run_in_background true?

agentic-workflow sets run_in_background true on all Task subagents so the main Claude Code conversation stays minimal. Agents write results to .claude/cache/agents/<stage>/ instead of returning full transcripts that would bloat context.

What is the difference between Task and TaskOutput in agentic-workflow?

agentic-workflow mandates the Task tool and explicitly avoids TaskOutput. TaskOutput would inject complete agent transcripts into the main thread, defeating the pattern's goal of keeping orchestration lightweight across long sessions.

Where do agentic-workflow subagents store their outputs?

agentic-workflow agents write outputs to .claude/cache/agents/<stage>/ directories. Subsequent agents read those staged files for injection, enabling a research-to-implementation pipeline without carrying full conversation history.

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