Runs agents from a predefined harness configuration, managing inputs, outputs, and inter-agent file communication.

Install

mkdir -p .claude/skills/run && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/11313" && unzip -o skill.zip -d .claude/skills/run && rm skill.zip

Installs to .claude/skills/run

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Invoke an agent from a designed harness. Reads .wrangler/harness.json to find the agent config, loads its system prompt, and spawns it via the Agent tool. Manages sprint directories and inter-agent communication files automatically. Usage: /wrangler:run <agent-name> Trigger: "run agent", "run harness", "에이전트 실행", "하네스 실행"
323 charsno explicit “when” triggerlonger than Claude Code's old 250-char listing cap (fine on current versions)
Advanced

Key capabilities

  • Read harness configuration
  • Spawn sub-agents
  • Manage sprint directories
  • Verify output files
  • Suggest next agent

How it works

It reads harness configurations to spawn isolated sub-agents that communicate exclusively through file-based handoffs.

Inputs & outputs

You give it
Agent name
You get back
Sub-agent execution results

When to use run

  • Run agent from harness
  • Execute sprint tasks
  • Automate sub-agent handoffs

About this skill

Wrangler: Run — Agent Runner

Dispatches a specific agent from the user's harness configuration. Manages sprint directories and inter-agent handoff files.

Architecture: Sub-Agent + File-Only Communication

Main Session (Orchestrator = you)
  │
  │  1. Read harness.json → identify agent + handoff config
  │  2. Read input files from .wrangler/sprint-N/
  │  3. Spawn sub-agent via Agent tool (separate context)
  │  4. Verify output files were created
  │  5. Suggest next agent
  │
  ├─ Agent(planner)   ← cannot see main session or other agents
  ├─ Agent(generator)  ← cannot see main session or other agents
  └─ Agent(evaluator)  ← cannot see main session or other agents

Key rules:

  • Each agent runs as a sub-agent via the Agent tool (separate context window)
  • Agents cannot see the main session conversation or each other's reasoning
  • The only communication channel between agents is .wrangler/sprint-N/ files
  • The orchestrator reads input files and passes them in the agent's prompt
  • The orchestrator never summarizes or interprets another agent's output — it passes file contents verbatim

Step 1: Load Harness Config

Read .wrangler/harness.json in the current project root.

  • If the file does not exist → Tell the user: "No harness found. Run /wrangler:design first to create one." Stop here.

Step 2: Determine Current Sprint

Read harness.json.currentSprint to get the sprint number (default: 1).

Ensure the sprint directory exists:

.wrangler/sprint-{currentSprint}/

If it doesn't exist, create it.


Step 3: Identify Target Agent

Check the skill argument for an agent name (e.g., /wrangler:run planner).

  • If no argument given → List available agents and ask: "Which agent do you want to run? Available agents:" Then list each agent with its role. Stop and wait.

  • If argument given → Look up the agent in harness.json.agents. If not found, show available agents and ask.


Step 4: Gather Input Files for This Agent

Using harness.json.workflow.handoffs, find all handoffs where to matches the target agent. These are the input files the agent needs.

For each matching handoff:

  1. Build the file path: .wrangler/sprint-{currentSprint}/{handoff.filename}
  2. If iterable: true, find the highest-numbered file (e.g., evaluator-to-generator--feedback-03.md)
  3. Read the file contents

Also read:

  • .wrangler/progress.md (if exists)
  • .wrangler/sprint-{currentSprint}/planner-to-generator--contract.md (if exists and agent is not planner)

If a required input file does not exist yet:

  • This is normal if the previous agent hasn't run yet
  • Note which files are missing and include that info in the agent prompt

Step 5: Determine Output Files for This Agent

Using harness.json.workflow.handoffs, find all handoffs where from matches the target agent. These are the output files the agent must write.

For each matching handoff:

  1. Build the expected output path: .wrangler/sprint-{currentSprint}/{handoff.filename}
  2. If iterable: true, determine the next number:
    • Count existing files matching the pattern
    • Next file = count + 1, zero-padded (01, 02, 03...)
    • Replace {n} in filename with the number

Step 6: Spawn the Agent

Read the agent's system prompt from .wrangler/{agent.promptFile}.

Construct and execute an Agent tool call:

Agent({
  description: "Wrangler: {agent-name} (sprint {currentSprint})",
  subagent_type: "{agent.subagentType}",
  model: "{agent.model}",
  prompt: `
{contents of the agent's promptFile}

---

## Sprint Info

- Sprint: {currentSprint}
- Sprint directory: .wrangler/sprint-{currentSprint}/

## Input Files

{for each input handoff file that exists:}
### {filename}
{file contents}

{for each input that is missing:}
### {filename} — NOT YET CREATED
(The previous agent has not run yet for this sprint.)

## Current Progress

{contents of progress.md, if exists}

## Output Requirements

You MUST write the following files when done:

{for each output handoff:}
- .wrangler/sprint-{currentSprint}/{resolved filename}
  Content: {artifact description}

## Additional Instructions

1. Write all output files to .wrangler/sprint-{currentSprint}/
2. Update .wrangler/progress.md with:
   - What you accomplished
   - Current sprint phase
   - Last agent: {agent-name}
3. Working directory: {current project root path}
`
})

Step 7: Post-Run Verification

After the agent completes:

7.1 Verify output files were created

Check that each expected output file exists in .wrangler/sprint-{currentSprint}/. If any are missing, warn the user.

7.2 Update progress tracking

Read .wrangler/progress.md and verify it was updated by the agent. If not, update it with:

- Last agent: {agent-name}
- Sprint: {currentSprint}
- Phase: {agent-name} completed
- Iteration: {current iteration count for feedback loops}

7.3 Check feedback loop (if evaluator just ran)

If the agent that just ran is the from side of a workflow.loops entry:

  1. Read the evaluator's latest feedback file
  2. Extract the score (look for "Overall Score: X / 100" or similar)
  3. Compare against loop.passThreshold:
    • Score >= threshold → "Score {score}/{threshold} — passed. Moving to sprint {currentSprint + 1}." Update harness.json.currentSprint to currentSprint + 1. Create new sprint directory: .wrangler/sprint-{newSprint}/
    • Score < threshold → Count how many feedback files exist for this sprint. If count >= loop.maxIterations: "Max iterations ({maxIterations}) reached. Consider adjusting criteria or moving on." Else: "Score {score}/{threshold}. Iteration {count}/{maxIterations}. Run /wrangler:run {loop.to} to iterate."

7.4 Suggest next step

Look at workflow.sequence to find the next agent after the one that just ran.

Display:

Sprint {currentSprint} status:
- {agent-name}: done
- {next-agent}: ready → /wrangler:run {next-agent}

Created files:
- .wrangler/sprint-{N}/{output-file-1}
- .wrangler/sprint-{N}/{output-file-2}

When not to use it

  • When no harness configuration exists

Prerequisites

.wrangler/harness.json

Limitations

  • Agents cannot see main session conversation

How it compares

It enforces strict file-based communication between sub-agents, preventing context leakage.

Compared to similar skills

run side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
run (this skill)04moNo flagsAdvanced
using-superpowers953moNo flagsBeginner
ultrawork112moNo flagsAdvanced
clawhub252moReviewIntermediate

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