Agent skill

Workflow Router

by parcadei in parcadei/Continuous-Claude-v3

Goal-based workflow orchestration - routes tasks to specialist agents based on user goals

MITAuto-check passedAgent Workflows

Install Workflow Router

skills CLI
$ npx skills add parcadei/Continuous-Claude-v3 --skill workflow-router -a claude-code

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

GitHub CLI
$ gh skill install parcadei/Continuous-Claude-v3 workflow-router --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/parcadei/Continuous-Claude-v3.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/workflow-router .claude/skills/workflow-router && 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
workflow-router
GitHub stars
3.9k
Used in
1 other repo
Token cost
~1.5k tokens
SKILL.md length
414 words
Files
1
Skills in repo
141
Repo updated
First seen
Licence
MIT

At a glance

Goal-based workflow orchestration - routes tasks to specialist agents based on user goals

  • Works in 5 steps: Goal Selection → Plan Detection → Resource Allocation → …
  • Agent Workflows work in your project
  • SKILL.md covers When to Use, Workflow Process, Agent Spawn Examples and Tips
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Workflow Router is an agent skill from parcadei/Continuous-Claude-v3. Goal-based workflow orchestration - routes tasks to specialist agents based on user goals

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows. The repository describes itself as: Context management for Claude Code. Hooks maintain state via ledgers and handoffs. MCP execution without context pollution. Agent orchestration with isolated context windows. The licence is MIT.

When your agent uses it

  • Agent Workflows work in your project

Example prompts

  • “/workflow-router”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Goal Selection
  2. Plan Detection
  3. Resource Allocation
  4. Specialist Mapping
  5. Confirmation

What it can do on your machine

Read from SKILL.md and the folder at commit d07ff4b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    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 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

Workflow Router loads about 1.5k tokens when it runs. Until then it costs about 26 tokens; SKILL.md has 414 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~26
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

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 passed

The automated check found no risky patterns in SKILL.md.

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 parcadei/Continuous-Claude-v3 at commit d07ff4b, republished under its MIT licence (© parcadei). 414 words, ~1,491 tokens.

Download SKILL.mdSave it as .claude/skills/workflow-router/SKILL.md (or your agent's skills folder).
name
workflow-router
description
Goal-based workflow orchestration - routes tasks to specialist agents based on user goals

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:

bash
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.

Show full SKILL.md (149 more words)Show less
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

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

Files

Just SKILL.md in .claude/skills/workflow-router of parcadei/Continuous-Claude-v3.

Open the folder on GitHubat commit d07ff4b

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in parcadei/Continuous-Claude-v3, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Workflow Router next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Hook Development for Claude Code Pluginsanthropics/claude-plugins-official38k11 repos~4.1kAutomated safety check: NotesApache-2.0
Using Superpowersfarm-fe/farm5.6k35 repos~1.4kAutomated safety check: PassMIT
Executing Plans Inlineobra/superpowers296k2 repos~5.1kAutomated safety check: PassMIT
Claude Code Agent Developmentanthropics/claude-plugins-official38k8 repos~2.8kAutomated safety check: PassApache-2.0

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Categories

Questions about Workflow Router

What does Workflow Router do?

Goal-based workflow orchestration - routes tasks to specialist agents based on user goals. Workflow Router is an agent skill from parcadei/Continuous-Claude-v3.

When should I use Workflow Router?

Workflow Router fits situations like: agent Workflows work in your project.

How do I install Workflow Router in Claude Code?

Run `npx skills add parcadei/Continuous-Claude-v3 --skill workflow-router -a claude-code`. Or copy the skill folder (.claude/skills/workflow-router in parcadei/Continuous-Claude-v3) into .claude/skills/workflow-router in your project. Claude Code loads it when a task matches its description.

How do I install Workflow Router in Codex?

Run `npx skills add parcadei/Continuous-Claude-v3 --skill workflow-router -a codex`. Or copy the skill folder (.claude/skills/workflow-router in parcadei/Continuous-Claude-v3) into .agents/skills/workflow-router in your project. Codex loads it when a task matches its description.

Can I use Workflow Router 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 parcadei/Continuous-Claude-v3 --skill workflow-router -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/workflow-router, .gemini/skills/workflow-router, .github/skills/workflow-router and .opencode/skills/workflow-router in your project.

What does Workflow Router need to run?

SKILL.md names no scripts, command-line tools or credentials: Workflow Router is instructions for the agent only.

Does Workflow Router 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 Workflow Router safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Workflow Router use?

Workflow Router 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 Workflow Router use?

About 1.5k tokens (SKILL.md is roughly 6k 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 Workflow Router?

Skills that share tags, products or a category with Workflow Router: MCP Server Builder (anthropics/skills, 180k stars), Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 38k stars), Using Superpowers (farm-fe/farm, 5.6k stars) and Executing Plans Inline (obra/superpowers, 296k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Workflow Router?

parcadei (a GitHub user) maintains it in parcadei/Continuous-Claude-v3, which has 3,940 GitHub stars. The repository holds 141 skills in this directory. The repository was last updated on January 26, 2026.

Source: parcadei/Continuous-Claude-v3 on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.