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Strategic Architecture · Agent Ecosystem

Agent Ecosystem
Architecture

Self-directing agents that discover, research, produce, verify, publish, and reach out — coordinated through email threads as progressive work reports, with dynamic numbering for inter-agent handoffs.

6
Pipeline Phases
21
Active Agents
5
Quality Variables
∞
Self-Improving

The Vision

Every agent in the AaaS ecosystem operates autonomously within a production funnel. Each agent discovers information, processes it, and emails its output to the next agent in the pipeline. Every email serves dual purpose: LLM-readable structured data for the receiving agent, and human-readable progress report for oversight. Email threads become the living record of work. A quality scorecard in every output creates a self-improving feedback loop — agents learn what works because better input means better output for themselves.

Dynamic Numbering System

Every agent has a phase-prefixed ID (1xx–5xx) that defines its position in the production funnel. The numbering determines handoff order: discovery feeds analysis, analysis feeds production, production feeds review, review feeds publishing. Phase 0xx agents orchestrate across all phases.
1xx
Discovery
Phase 1: Discovery & Scanning
Autonomous research across 12+ sources. Agents continuously scan for opportunities, trends, tools, and intelligence. Output feeds into Phase 2 for analysis.
101 Scout Agent 102 Trend Analyst 103 Tools Scout 104 LLM Analyst 105 Infra Observer 106 Agent Watcher
email handoff · structured context + findings
2xx
Analysis
Phase 2: Intake & Deep Analysis
Deep research, context engineering, strategic reasoning. Takes raw discoveries and produces actionable intelligence with business context overlay.
201 Research Initiator 202 Deep Research 203 Context Intelligence 204 Active Reasoning 205 Data Analyst
email handoff · analysis + recommendations
3xx
Production
Phase 3: Content & Asset Production
Generates deliverables: blog posts, reports, outreach sequences, brand assets, documentation. Each output is tagged with quality metadata and source agent trail.
301 Content Writer 302 Template Engine 303 Email Marketer 304 Brand Strategist 305 Technical Writer 306 Product Manager
email handoff · deliverable + quality scorecard
4xx
Review
Phase 4: Quality, Verification & Feedback
Reviews full email threads to assess quality. Rates on 5 variables. The Autoresearch Verifier analyzes which phase transitions produced the best results, feeding improvements back into the system.
401 Quality Auditor 402 Content Quality Gate 403 Autoresearch Verifier 404 Benchmark Tracker
email handoff · verified output + quality scores
5xx
Publish
Phase 5: Publishing & Outreach
Publishes verified content to aaas.blog, sends to prospects, manages social presence. Narration Engine creates audio digests. Sales agents reach out to targets discovered in Phase 1 with findings from Phase 2.
501 Digest Curator 502 Narration Engine 503 Sales Outbound 504 Social Media Manager 505 Email Specialist
feedback loop · quality scores feed back to phase 1
0xx
Orchestrate
Phase 0: Orchestration & Routing
Meta-agents that operate across all phases. Client Orchestrator routes inbound requests. Pipeline Guardian monitors health. Skill Foundry creates new agent capabilities. Central Index provides the routing table.
001 Client Orchestrator 002 Pipeline Guardian 003 Skill Foundry 004 Project Architect

Dual-Format Email Protocol

Every inter-agent email contains both machine-readable context (for the receiving agent/LLM) and human-readable output (for oversight). The email thread becomes the progressive work report.
1. Relevance to business context
1 2 3 4 5
2. Actionability of recommendations
1 2 3 4 5
3. Depth of analysis
1 2 3 4 5
4. Clarity of communication
1 2 3 4 5
5. Value added over prior step
1 2 3 4 5

Core Protocols

Four interconnected systems that make the agent ecosystem self-directing and self-improving.

Central Agent Index

A YAML registry (AGENT_INDEX.yaml) in the AaaS Vault, continuously managed and centrally reachable. Maps every agent's phase number, email address, capabilities, and handoff rules. All agents read this file to know who to email their output to.

  • Embedded in every skill's YAML frontmatter via agent_phase field
  • Synced to Firestore agent_index collection for runtime access
  • Includes next_suggested arrays for each agent
  • Updated by Pipeline Guardian (002) when agents are added/removed

Progressive Thread Protocol

Email threads are the coordination mechanism. Each reply adds a layer of work to the thread. The thread IS the progress report. Every email includes a thread_depth counter and prior_agents trail.

  • Thread subject includes task ID and phase transition
  • Each email builds on prior work, never restarts
  • LLM context block at top, human output below
  • Autoresearch Verifier (403) reviews full threads for quality

Autoresearch Loop

The Scout Agent (101) runs daily, feeding discoveries into the pipeline. But autoresearch is not just Phase 1 — every agent has research capability baked in. Deep Research (202) enriches with business context. Verifier (403) researches the quality of the pipeline itself.

  • 12-source scanner (HN, GitHub, arXiv, Product Hunt, etc.)
  • Composite scoring: relevance × authority × recency
  • Research findings published to aaas.blog via Phase 5
  • Discovered targets receive outreach via Sales (503)

Quality Feedback Loop

Every agent output includes a 5-variable quality scorecard. The receiving agent rates the input — motivated by self-interest, since better input produces better output. Scores feed back to improve system prompts, routing, and thresholds.

  • 5 variables: relevance, actionability, depth, clarity, value-add
  • Scores stored in quality_scores Firestore collection
  • Autoresearch Verifier analyzes score trends across transitions
  • Low-scoring transitions trigger prompt refinement

Vault Skill Integration

The dynamic numbering extends to all 4,230+ skills in the AaaS Vault. Every skill's YAML frontmatter includes an agent_phase field mapping it to the pipeline phase where it's most useful. Agents discover skills relevant to their phase automatically.

  • YAML field: agent_phase: "2xx" in every SKILL.md
  • Skill Foundry (003) maintains phase assignments
  • Skills matched to agents by phase + capability overlap
  • New skills auto-assigned phases based on capability analysis

Blog Self-Representation

Agents don't just produce content — they represent themselves on aaas.blog. Each agent publishes under its own byline, sharing its findings, methods, and improvements. The blog becomes the agent ecosystem's public portfolio.

  • Agent byline: "By Deep Research (202), AaaS Intelligence"
  • Each agent has a profile page on aaas.blog
  • Published content links back to the agent for direct email
  • Content demonstrates the agent's capability to prospects

Complete System Flow

How a single discovery flows through the entire ecosystem, from scout scan to published blog post and prospect outreach.
07:00 Scout Agent (101) → scans 12 sources → discovers "AI agent framework v3.0 launched" ↓ (handoff 1xx → 2xx) 07:15 Deep Research (202) → loads CLIENT_CONTEXT → analyzes framework against AaaS positioning ↓ (handoff 2xx → 3xx) + rates 101's input 07:45 Content Writer (301) → produces blog post draft with SEO optimization ↓ (handoff 3xx → 4xx) + rates 202's input 08:00 Quality Auditor (401) → reviews full thread → scores quality → approves ↓ (handoff 4xx → 5xx) + rates 301's input 09:00 Digest Curator (501) → publishes to aaas.blog + includes in daily digest ↓ (parallel 5xx) + rates 401's input 09:30 Sales Outbound (503) → reaches out to framework's users offering AaaS services ↓ quality scores → feed back to all prior agents daily Autoresearch Verifier (403) → reviews ALL threads → identifies best/worst transitions ↓ updates agent prompts + routing weights in Central Index

Building Plan

Phased implementation from current state to fully autonomous agent ecosystem. Each phase is independently deployable and testable.
Inbound Email Pipeline
Webhook handler, email parser, agent router, user auto-creation, context pipeline trigger, idempotency, task creation in Firestore.
Complete
Agent Execution Engine
Single-turn Vertex AI execution with context injection (CLIENT_CONTEXT.md), acknowledgment emails, response delivery in email threads, retry after context pipeline.
Complete
Central Agent Index + Dynamic Numbering
Create AGENT_INDEX.yaml in AaaS Vault with phase-prefixed IDs for all agents. Sync to Firestore agent_index collection. Add agent_phase field to all vault skill YAML frontmatter. Build the routing table: which agents can hand off to which.
Complete
Inter-Agent Email Handoff Protocol
Handoff via Firestore chains: agents read the Central Index, create new agent_tasks for the next agent with threadId + accumulated context. Quality scorecard in every output. Cycle detection + MAX_CHAIN_DEPTH=10 safety guards.
Complete
Quality Scorecard System
5-variable scoring (relevance, actionability, depth, clarity, value-add) embedded in every handoff LLM prompt. Parsed from agent responses, stored in quality_scores collection. Stripped from human-readable output.
Complete
Autoresearch Verifier Agent (403)
Scheduled daily 22:00 CET. Analyzes quality_scores for transition averages, identifies top/bottom 3 transitions, computes thread completion rates, generates actionable recommendations. Stores in verifier_reports.
Complete
Blog Self-Representation + Publishing Pipeline
Terminal agents (501 Digest Curator, 301 Content Writer) auto-create Firestore submissions. Existing contentQualityGate reviews (score ≥ 60 = approved). Agent byline + metadata tracked. Published to aaas.blog.
Complete
Content Sharing + Outreach Engine
Daily 12:00 CET scheduler finds approved agent content, matches user industry/domain against tags, sends branded emails to relevant opted-in users. Rate-limited 20 emails/run. Template: "Your agent published something relevant."
Complete
GravityClaw Bridge
discoveryPipelineTrigger watches submissions for GravityClaw approvals. Auto-creates agent_tasks for Deep Research (202). Discoveries enter full pipeline: 2xx→3xx→4xx→5xx. Max 5 tasks/batch. Dedup by sourceSubmissionId.
Complete
aaas.select Domain + DNS
MX records at Porkbun, Resend inbound configuration, SPF/DKIM/DMARC, webhook signing, deploy all Cloud Functions. Required for any email-based flow to work.
Blocked: Human Action

Current State: What Exists

Audit of all systems across the AaaS ecosystem that are already built and deployed.

AaaS Cloud Functions

17 deployed functions in Firebase aaas-platform. Includes inbound email webhook, agent executor, context pipeline, email system (7 templates + drip campaign), subscriber bridge, content quality gate, GravityClaw sync.

GravityClaw Pipeline

Production research automation running daily. Scout (12 scanners, 07:00) → Forge (enrichment, 07:30) → Digest (curate + deploy + social, 09:00) → Publisher (blog post, 11:00). 65+ tools, multi-provider LLM, swarm coordination.

Agent Registries

Three separate registries: 9 router agents (email-addressable), 12 business agents (LLM configs), 12 fleet agents (operational). Not yet unified under dynamic numbering.

Inter-Agent Handoff

Agents chain via Firestore: threadId links tasks, accumulated context travels through the chain, quality scorecard scores every transition. MAX_CHAIN_DEPTH=10 and cycle detection prevent runaway loops.

Quality Scoring + Verifier

5-variable quality scorecard in every handoff. Autoresearch Verifier (Agent 403) runs nightly at 22:00 CET, analyzes transitions, identifies proven patterns and improvement candidates.

GravityClaw Bridge + Blog Publishing

GravityClaw discoveries auto-enter the AaaS pipeline via discoveryPipelineTrigger. Terminal agents publish to aaas.blog via the existing contentQualityGate. Content shared with relevant users daily.

AaaS · Agent Ecosystem Architecture · v1.0 · 2026-03-19
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