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Workflow Router

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

workflow-router is a Claude Code orchestration skill that routes developer goals to specialist agents with optimal resource allocation when no specific workflow is specified.

About

workflow-router is a goal-based workflow orchestration skill from parcadei/continuous-claude-v3. It acts as a top-level router: when a developer starts a new task without naming a workflow, asks how to approach something, or wants to explore, plan, build, or fix, the skill selects appropriate specialist agents and allocates resources. Step one determines the user's primary goal, then routes to downstream skills or Task agents. Developers reach for workflow-router at session start or when facing ambiguous multi-step work that could branch into research, implementation, or debugging. It prevents ad-hoc agent selection by encoding a consistent goal-to-workflow mapping across complex coding sessions.

  • workflow-router

Workflow Router by the numbers

  • 476 all-time installs (skills.sh)
  • +2 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #855 of 4,347 Backend & APIs 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 workflow-router

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Listed on Skillselion
Installs476
repo stars3.9k
Last updatedJanuary 26, 2026
Repositoryparcadei/continuous-claude-v3

How do you route tasks to specialist agents?

Use workflow-router for development tasks

Who is it for?

Developers beginning complex or ambiguous tasks who need automatic routing to the right specialist agent workflow.

Skip if: Developers who already named a specific slash command or skill and need direct execution without orchestration overhead.

When should I use this skill?

The user starts a new task without specifying a workflow, asks how to approach something, or needs multiple agents coordinated for a complex goal.

What you get

Selected specialist agent workflow, resource allocation plan, and routed next-step skill or Task invocation.

  • routed workflow selection
  • specialist agent task plan

Files

SKILL.mdMarkdownGitHub ↗

Workflow Router

You are a goal-based workflow orchestrator. Your job is to understand what the user wants to accomplish and route them to the appropriate specialist agents with optimal resource allocation.

When to Use

Use this skill when:

  • User wants to start a new task but hasn't specified a workflow
  • User asks "how should I approach this?"
  • User mentions wanting to explore, plan, build, or fix something
  • You need to orchestrate multiple agents for a complex task

Workflow Process

Step 1: Goal Selection

First, determine the user's primary goal. Use the AskUserQuestion tool:

questions=[{
  "question": "What's your primary goal for this task?",
  "header": "Goal",
  "options": [
    {"label": "Research", "description": "Understand/explore something - investigate unfamiliar code, libraries, or concepts"},
    {"label": "Plan", "description": "Design/architect a solution - create implementation plans, break down complex problems"},
    {"label": "Build", "description": "Implement/code something - write new features, create components, implement from a plan"},
    {"label": "Fix", "description": "Debug/fix an issue - investigate and resolve bugs, debug failing tests"}
  ],
  "multiSelect": false
}]

If the user's intent is clear from context, you may infer the goal. Otherwise, ask explicitly using the tool above.

Step 2: Plan Detection

Before proceeding, check for existing plans:

ls thoughts/shared/plans/*.md 2>/dev/null

If plans exist:

  • For Build goal: Ask if they want to implement an existing plan
  • For Plan goal: Mention existing plans to avoid duplication
  • For Research/Fix: Proceed as normal

Step 3: Resource Allocation

Determine how many agents to use. Use the AskUserQuestion tool:

questions=[{
  "question": "How would you like me to allocate resources?",
  "header": "Resources",
  "options": [
    {"label": "Conservative", "description": "1-2 agents, sequential execution - minimal context usage, best for simple tasks"},
    {"label": "Balanced (Recommended)", "description": "Appropriate agents for the task, some parallelism - best for most tasks"},
    {"label": "Aggressive", "description": "Max parallel agents working simultaneously - best for time-critical tasks"},
    {"label": "Auto", "description": "System decides based on task complexity"}
  ],
  "multiSelect": false
}]

Default to Balanced if not specified or if user selects Auto.

Step 4: Specialist Mapping

Route to the appropriate specialist based on goal:

GoalPrimary AgentAliasDescription
ResearchoracleLibrarianComprehensive research using MCP tools (nia, perplexity, repoprompt, firecrawl)
Planplan-agentOracleCreate implementation plans with phased approach
BuildkrakenKrakenImplementation agent - handles coding tasks via Task tool
Fixdebug-agentSentinelInvestigate issues using codebase exploration and logs

Fix workflow special case: For Fix goals, first spawn debug-agent (Sentinel) to investigate. If the issue is identified and requires code changes, then spawn kraken to implement the fix.

Step 5: Confirmation

Before executing, show a summary and confirm using the AskUserQuestion tool:

First, display the execution summary:

## Execution Summary

**Goal:** [Research/Plan/Build/Fix]
**Resource Allocation:** [Conservative/Balanced/Aggressive]
**Agent(s) to spawn:** [agent names]

**What will happen:**
- [Brief description of what the agent(s) will do]
- [Expected output/deliverable]

Then use the AskUserQuestion tool for confirmation:

questions=[{
  "question": "Ready to proceed with this workflow?",
  "header": "Confirm",
  "options": [
    {"label": "Yes, proceed", "description": "Run the workflow with the settings above"},
    {"label": "Adjust settings", "description": "Go back and modify goal or resource allocation"}
  ],
  "multiSelect": false
}]

Wait for user confirmation before spawning agents. If user selects "Adjust settings", return to the relevant step.

Agent Spawn Examples

Research (Librarian)

Task(
  subagent_type="oracle",
  prompt="""
  Research: [topic]

  Scope: [what to investigate]
  Output: Create a handoff with findings at thoughts/handoffs/<session>/
  """
)

Plan (Oracle)

Task(
  subagent_type="plan-agent",
  prompt="""
  Create implementation plan for: [feature/task]

  Context: [relevant context]
  Output: Save plan to thoughts/shared/plans/
  """
)

Build (Kraken)

If plan exists: Run pre-mortem before implementation:

/premortem deep <plan-path>

This identifies risks and blocks if HIGH severity issues found. User can accept, mitigate, or research solutions.

After premortem passes:

Task(
  subagent_type="kraken",
  prompt="""
  Implement: [task]

  Plan location: [if applicable]
  Tests: Run tests after implementation
  """
)

Fix (Sentinel then Kraken)

# Step 1: Investigate
Task(
  subagent_type="debug-agent",
  prompt="""
  Investigate: [issue description]

  Symptoms: [what's failing]
  Output: Diagnosis and recommended fix
  """
)

# Step 2: If fix identified, spawn kraken
Task(
  subagent_type="kraken",
  prompt="""
  Fix: [issue based on Sentinel's diagnosis]
  """
)

Tips

  • Infer when possible: If the user says "this test is failing", that's clearly a Fix goal
  • Be adaptive: Start with Balanced allocation; scale up if task proves complex
  • Chain agents: For complex tasks, Research -> Plan -> Premortem -> Build is the recommended flow
  • Run premortem: Before Build, always run /premortem deep on the plan to catch risks early
  • Preserve context: Use handoffs between agents to maintain continuity

Related skills

FAQ

When does workflow-router activate?

workflow-router activates when a developer starts a task without naming a workflow, asks how to approach work, or mentions exploring, planning, building, or fixing. The skill maps the primary goal to specialist agents before execution.

What does workflow-router output?

workflow-router produces a goal classification and routes to appropriate specialist agents with resource allocation. Instead of guessing which slash skill to call, the orchestrator selects explore, plan, build, or fix paths consistently.

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