Teaches Claude when to spawn implementation agents instead of burning context in the main conversation. The core insight is simple: for multi-file changes or plan phases, spin up an agent that reads files and implements in its own context, then reports back a summary. Saves you from hitting token limits on complex features. Includes a decision table (agents for new features, skip for one-line fixes) and example prompts showing how to delegate work. Best used when you're working through a multi-phase plan or building something that touches several files. The alternative is watching your context window fill up with file contents you read once and never reference again.

skills.sh installs
525
GitHub stars
3.9K
last updated
Aug 21, 2026

Install

$ npx -y skills add parcadei/continuous-claude-v3 --skill agent-orchestration --agent claude-code

Installs into .claude/skills of the current project.

Files

Agent Orchestration Rules

When the user asks to implement something, use implementation agents to preserve main context.

The Pattern

Wrong - burns context:

Main: Read files → Understand → Make edits → Report
      (2000+ tokens consumed in main context)

Right - preserves context:

Main: Spawn agent("implement X per plan")
      ↓
Agent: Reads files → Understands → Edits → Tests
      ↓
Main: Gets summary (~200 tokens)

When to Use Agents

Task TypeUse Agent?Reason
Multi-file implementationYesAgent handles complexity internally
Following a plan phaseYesAgent reads plan, implements
New feature with testsYesAgent can run tests
Single-line fixNoFaster to do directly
Quick config changeNoOverhead not worth it

Key Insight

Agents read their own context. Don't read files in main chat just to understand what to pass to an agent - give them the task and they figure it out.

Example Prompt

Implement Phase 4: Outcome Marking Hook from the Artifact Index plan.

Sponsors

Details

Repository
github.com/parcadei/continuous-claude-v3
Categories
AI & Agent Building, Automation & Workflows
First seen
Jun 3, 2026

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