Multi-Agent Content Pipeline for Claude Code with Quality Gates

✍️ OpenClawRadar📅 Published: March 29, 2026🔗 Source
Multi-Agent Content Pipeline for Claude Code with Quality Gates
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Pipeline Architecture

The pipeline uses six specialized agents organized into two phases with strict handoff protocols.

Phase 1 (parallel execution):

  • Research Agent: handles web search, topic analysis, and competitor content review
  • Analytics Agent: pulls data from GSC, GA4, and DataForSEO

Phase 2 (sequential execution):

  • Writer Agent: creates drafts from research briefs
  • Editor Agent: checks quality, accuracy, brand voice, and humanization
  • SEO/GEO Agent: handles keyword optimization, schema markup, and geographic readiness
  • Master Agent: reviews all outputs, produces quality scores and flags, and presents the final draft

Quality Gate System

The pipeline includes explicit quality checks between agent handoffs:

  • Gate 1: Verifies both research and analytics files exist with COMPLETE status before writer begins
  • Gate 2: Checks word count is within 50% of target and meta sections are present before editing starts
  • Similar gates continue through all stages

Without these gates, failures in early stages can propagate silently through the pipeline, only being caught at the final review if at all. The gates make failures "loud and early."

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Key Implementation Details

The system uses a structured file system for agent communication:

  • Agents write to shared files in predictable locations (e.g., .claude/pipeline/research.md, draft.md)
  • Downstream agents know exactly where to look for previous stage outputs
  • This prevents the fragility of implicit handoffs where "Claude will figure out what the previous step produced"

Individual agents can be re-run without restarting the entire pipeline using commands like:

/run-agent writer "rewrite with a more technical tone"
/run-agent seo "re-optimise for keyword: [new keyword]"

This allows fixing bad drafts without invalidating good research work.

Publishing Control

The pipeline includes a hard stop before publishing. After the Master Agent produces its summary with quality scores and flags, the system halts completely. Nothing publishes until the user manually types "approved." This prevents accidental publication without proper review.

📖 Read the full source: r/ClaudeAI

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👀 See Also