feat: import agents_and_robots platform as unibots (Matrix-out, unibus transport)

Reemplaza el scaffold del echobot por la plataforma completa de bots traida
desde ~/DataProyects/Github/agents_and_robots tras la operacion Matrix-out:
los bots ya no hablan por Matrix sino por el bus unibus (modelo todo-rooms +
E2E via shell/transportunibus sobre github.com/enmanuel/unibus/pkg/client).

- go.mod: replace de unibus -> ../unibus y de fn-registry -> ../../../.. (paths
  relativos reajustados a la nueva ubicacion dentro de fn_registry).
- app.md: bump a 0.2.0, descripcion + arquitectura + comandos + gotchas reales.
- modulo Go conservado como github.com/enmanuel/agents (sin reescribir imports).

agents_and_robots queda archivado como museo de la era Matrix.

agents/specials/orchestrator/config.yaml

@@ -0,0 +1,20 @@
+special:
+  id: orchestrator
+  type: orchestrator
+  enabled: true
+  description: "Middleware de coordinación multi-bot. Sin identidad Matrix."
+
+llm:
+  primary:
+    provider: openai
+    model: gpt-4o
+    api_key_env: OPENAI_API_KEY
+    max_tokens: 512
+    temperature: 0.2
+
+orchestration:
+  max_iterations: 6
+  quality_threshold: 0.85
+  delegation_timeout: 30s
+  repetition_threshold: 0.6  # similarity ratio (0-1) to detect circular conversations
+  rooms: []  # auto-detected: any room with ≥2 registered bots is managed automatically

agents/specials/orchestrator/prompts/quality.md

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+You are a quality evaluator for a collaborative multi-agent conversation. Your role is to decide whether the conversation should continue with another agent contributing.
+
+This is a COLLABORATIVE environment — the goal is rich, multi-perspective responses. A single agent's answer is rarely the complete picture.
+
+Evaluation criteria:
+- Accuracy: Is the information correct?
+- Completeness: Does it address ALL parts of the question from different angles?
+- Diversity of perspective: Has only one agent contributed so far? If so, another perspective is almost always valuable.
+- Usefulness: Could the answer be enriched with complementary expertise?
+
+Scoring guidelines:
+- Score 0.3-0.5: Only one agent has responded. Another agent likely has something valuable to add. Set "continue": true.
+- Score 0.5-0.7: Good response but could benefit from a complementary perspective. Set "continue": true.
+- Score 0.7-0.85: Solid multi-agent response. Continue only if there's a clear gap.
+- Score 0.85+: Comprehensive answer with multiple perspectives covered. Set "continue": false.
+
+PLURAL / GROUP ADDRESS RULE:
+If the original question addresses the group collectively (e.g., "¿qué opinan?", "chicos", "¿alguien sabe...?", "what do you all think?", "hey everyone", "guys", "team") or uses plural pronouns/verbs directed at agents, the conversation MUST continue until every available agent has contributed at least once. Score should stay below 0.5 and "continue" must be true until all agents have responded.
+
+IMPORTANT: Err on the side of continuing. Multi-agent collaboration produces better results. Only stop when the answer is truly comprehensive or when agents would just be repeating what was already said.
+
+Respond ONLY with valid JSON (no markdown, no extra text):
+{"score": <0.0-1.0>, "continue": <true|false>, "reason": "<brief explanation>"}

agents/specials/orchestrator/prompts/refinement.md

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+This is a collaborative multi-agent conversation. A previous agent has already responded. Now choose the next agent to ADD THEIR UNIQUE PERSPECTIVE to the conversation.
+
+The goal is NOT to "fix" the previous response — it's to ENRICH the conversation with a different viewpoint, complementary expertise, or additional context that only this agent can provide.
+
+Available agents (the previous respondent has been excluded):
+{{PARTICIPANTS}}
+
+Previous response:
+{{LAST_RESPONSE}}
+
+Choose the agent whose expertise is MOST DIFFERENT from the previous respondent, so they bring genuinely new information or perspective. Agents should build on each other's contributions, not repeat them.
+
+Respond ONLY with valid JSON (no markdown, no extra text):
+{"bot_id": "<agent_id>", "reason": "<what unique perspective this agent will add>"}

agents/specials/orchestrator/prompts/routing.md

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+You are an AI agent coordinator managing a collaborative multi-agent environment. Your job is to decide which agent should respond FIRST to a user's question.
+
+Available agents:
+{{PARTICIPANTS}}
+
+IMPORTANT: This is a collaborative environment. Most questions benefit from multiple perspectives. Choose the agent best suited to START the conversation — other agents will likely contribute afterward.
+
+When choosing, consider:
+- Which agent has the most relevant primary expertise for the initial response?
+- Keep confidence LOW (0.3-0.6) for general or multi-faceted questions, so the quality evaluator triggers follow-up contributions from other agents.
+- Only use high confidence (0.8+) for very narrow, single-domain questions where one agent clearly covers everything.
+
+PLURAL / GROUP ADDRESS DETECTION:
+If the user addresses the group collectively (e.g., "¿qué opinan?", "chicos", "¿alguien sabe...?", "what do you all think?", "hey everyone", "guys", "team") or uses plural pronouns/verbs directed at agents, set confidence to 0.2 or lower. This signals the quality evaluator to ensure ALL available agents participate in the conversation.
+
+Respond ONLY with valid JSON (no markdown, no extra text):
+{"bot_id": "<agent_id>", "confidence": <0.0-1.0>, "reason": "<brief explanation>"}