feat(config): T3 backend/frontend → senior devs; update agency-agents submodule

T3 squad leads now use dedicated senior roles instead of sharing
architects with T2:
- T3 backend: backend-architect → senior-backend-developer
- T3 frontend: frontend-architect → senior-frontend-developer

Clean tier separation:
  T2 = architects (design)
  T3 = senior devs (lead + implement-or-delegate)
  T4 = developers (pure implementation)

Depends on: coding-with-hans-heinemann/agency-agents#2

adapters/llm/anthropic.py

@@ -10,8 +10,6 @@ from __future__ import annotations
 
 import os
 
-import anthropic
-
 from adapters.base.llm import LLMAdapter
 
 
@@ -57,6 +55,14 @@ class AnthropicAdapter(LLMAdapter):
         ValueError
             If ANTHROPIC_API_KEY is not set in the environment.
         """
+        try:
+            import anthropic as _anthropic
+        except ModuleNotFoundError as exc:
+            raise ImportError(
+                "The 'anthropic' package is required for AnthropicAdapter. "
+                "Install it with: pip install anthropic"
+            ) from exc
+
         self._config = config
         api_key = os.environ.get("ANTHROPIC_API_KEY")
         if not api_key:
@@ -64,7 +70,7 @@ class AnthropicAdapter(LLMAdapter):
                 "ANTHROPIC_API_KEY environment variable is not set. "
                 "Export it before running the-agency."
             )
-        self._client = anthropic.Anthropic(api_key=api_key)
+        self._client = _anthropic.Anthropic(api_key=api_key)
         self._models_cfg: dict = config.get("models", {})
         self._default_max_tokens: int = self._models_cfg.get("default_max_tokens", 4096)
         self._default_temperature: float = self._models_cfg.get("default_temperature", 0)

config/role_registry.yaml

@@ -2,33 +2,49 @@ t1:
   default: agents/strategy/nexus-strategy.md
 
 t2:
-  backend:  agents/engineering/engineering-software-architect.md
+  backend:  agents/engineering/engineering-backend-architect.md
-  frontend: agents/engineering/engineering-software-architect.md
+  frontend: agents/engineering/engineering-frontend-architect.md
   infra:    agents/engineering/engineering-devops-automator.md
   data:     agents/engineering/engineering-data-engineer.md
+  ai:       agents/engineering/engineering-software-architect.md
+  security: agents/engineering/engineering-security-engineer.md
+  mobile:   agents/engineering/engineering-software-architect.md
   default:  agents/engineering/engineering-software-architect.md
 
 t3:
-  backend:  agents/engineering/engineering-senior-developer.md
+  backend:  agents/engineering/engineering-senior-backend-developer.md
-  frontend: agents/engineering/engineering-senior-developer.md
+  frontend: agents/engineering/engineering-senior-frontend-developer.md
   infra:    agents/engineering/engineering-sre.md
-  default:  agents/engineering/engineering-senior-developer.md
+  data:     agents/engineering/engineering-data-engineer.md
+  ai:       agents/engineering/engineering-ai-engineer.md
+  security: agents/engineering/engineering-security-engineer.md
+  mobile:   agents/engineering/engineering-mobile-app-builder.md
+  database: agents/engineering/engineering-database-optimizer.md
+  devops:   agents/engineering/engineering-sre.md
+  docs:     agents/engineering/engineering-technical-writer.md
+  default:  agents/engineering/engineering-backend-developer.md
 
 t4:
   frontend:  agents/engineering/engineering-frontend-developer.md
-  backend:   agents/engineering/engineering-backend-architect.md
+  backend:   agents/engineering/engineering-backend-developer.md
   database:  agents/engineering/engineering-database-optimizer.md
   devops:    agents/engineering/engineering-devops-automator.md
   mobile:    agents/engineering/engineering-mobile-app-builder.md
   ai:        agents/engineering/engineering-ai-engineer.md
   security:  agents/engineering/engineering-security-engineer.md
   docs:      agents/engineering/engineering-technical-writer.md
-  default:   agents/engineering/engineering-senior-developer.md
+  data:      agents/engineering/engineering-data-engineer.md
+  embedded:  agents/engineering/engineering-embedded-firmware-engineer.md
+  default:   agents/engineering/engineering-backend-developer.md
 
 t5:
-  code:        agents/engineering/engineering-code-reviewer.md
+  code:          agents/engineering/engineering-code-reviewer.md
-  integration: agents/testing/testing-reality-checker.md
+  integration:   agents/testing/testing-reality-checker.md
-  api:         agents/testing/testing-api-tester.md
+  api:           agents/testing/testing-api-tester.md
-  performance: agents/testing/testing-performance-benchmarker.md
+  performance:   agents/testing/testing-performance-benchmarker.md
-  security:    agents/engineering/engineering-security-engineer.md
+  security:      agents/engineering/engineering-security-engineer.md
-  default:     agents/engineering/engineering-code-reviewer.md
+  accessibility: agents/testing/testing-accessibility-auditor.md
+  e2e:           agents/testing/testing-evidence-collector.md
+  frontend:      agents/testing/testing-accessibility-auditor.md
+  data:          agents/testing/testing-reality-checker.md
+  default:       agents/engineering/engineering-code-reviewer.md

config/team.yaml

@@ -7,7 +7,17 @@ adapters:
   llm: anthropic
   vcs: github
   notify: openclaw
-  runtime: openclaw
+
+adapter_registry:
+  llm:
+    anthropic: "adapters.llm.anthropic:AnthropicAdapter"
+  vcs:
+    github: "adapters.vcs.github:GitHubAdapter"
+  notify:
+    openclaw: "adapters.notify.openclaw:OpenClawNotifyAdapter"
+  runtime:
+    openclaw: "adapters.runtime.openclaw:OpenClawRuntimeAdapter"
+    claude_code: "adapters.runtime.claude_code:ClaudeCodeRuntimeAdapter"
 
 models:
   default_max_tokens: 4096

core/team_runner.py

@@ -5,6 +5,12 @@ Top-level orchestration entry point for the-agency pipeline.
 The TeamRunner loads team.yaml, builds the adapter registry, and drives the
 full T1 → T2 → T3 → T4 → T5 dispatch loop with escalation handling.
 
+Runtime adapters are config-driven: every string-valued key in the top-level
+``runtime:`` section of team.yaml is instantiated as a RuntimeAdapter and
+stored in ``self._runtimes[name]``.  Non-string values (e.g. ``native_teams:
+false``) are silently skipped.  Dispatch routing uses
+``brief.preferred_runtime`` to look up the right adapter at call time.
+
 CLI usage::
 
     python -m core.team_runner --config config/team.yaml [--dry-run] [--verbose]
@@ -52,7 +58,7 @@ _TIER_CAPABILITIES: dict[int, str] = {
     1: "reasoning-heavy",
     2: "reasoning-heavy",
     3: "capable",
-    4: "capable",
+    4: "fast-cheap",
     5: "fast-cheap",
 }
 
@@ -65,18 +71,16 @@ _TIER_CAPABILITIES: dict[int, str] = {
 # enabling third-party adapters without touching this file.
 # ---------------------------------------------------------------------------
 
-_LLM_ADAPTERS: dict[str, str] = {
+# Adapter registries are loaded from team.yaml at runtime (adapter_registry section).
-    "anthropic": "adapters.llm.anthropic:AnthropicAdapter",
+# Fallback built-ins are used only if team.yaml doesn't define adapter_registry.
-}
+_BUILTIN_ADAPTER_REGISTRY: dict[str, dict[str, str]] = {
-_VCS_ADAPTERS: dict[str, str] = {
+    "llm": {"anthropic": "adapters.llm.anthropic:AnthropicAdapter"},
-    "github": "adapters.vcs.github:GitHubAdapter",
+    "vcs": {"github": "adapters.vcs.github:GitHubAdapter"},
-}
+    "notify": {"openclaw": "adapters.notify.openclaw:OpenClawNotifyAdapter"},
-_NOTIFY_ADAPTERS: dict[str, str] = {
+    "runtime": {
-    "openclaw": "adapters.notify.openclaw:OpenClawNotifyAdapter",
+        "openclaw": "adapters.runtime.openclaw:OpenClawRuntimeAdapter",
-}
+        "claude_code": "adapters.runtime.claude_code:ClaudeCodeRuntimeAdapter",
-_RUNTIME_ADAPTERS: dict[str, str] = {
+    },
-    "openclaw": "adapters.runtime.openclaw:OpenClawRuntimeAdapter",
-    "claude_code": "adapters.runtime.claude_code:ClaudeCodeRuntimeAdapter",
 }
 
 
@@ -151,11 +155,23 @@ class TeamRunner:
         config_path : Path to team.yaml.
         dry_run     : When True, skip LLM calls, VCS commits, and notifications.
                       All planned actions are logged at INFO level.
+
+        Runtime adapters are built from the top-level ``runtime:`` section of
+        team.yaml.  Each string-valued key becomes an entry in
+        ``self._runtimes``; non-string values (e.g. ``native_teams: false``)
+        are ignored.  Adding a new runtime type requires only a new key in
+        team.yaml — no changes to TeamRunner are needed.
         """
         self._dry_run = dry_run
 
         self._config = self._load_yaml(config_path)
         self._role_registry = self._load_yaml("config/role_registry.yaml")
+        # Merge config-defined adapter_registry over built-in fallbacks.
+        self._adapter_registry: dict[str, dict[str, str]] = {
+            k: {**v} for k, v in _BUILTIN_ADAPTER_REGISTRY.items()
+        }
+        for kind, entries in self._config.get("adapter_registry", {}).items():
+            self._adapter_registry.setdefault(kind, {}).update(entries)
         self._escalation = EscalationHandler()
 
         run_id = str(uuid.uuid4())
@@ -165,19 +181,27 @@ class TeamRunner:
         adapter_cfg: dict = self._config.get("adapters", {})
         runtime_cfg: dict = self._config.get("runtime", {})
 
-        self._llm: LLMAdapter = self._build_llm(adapter_cfg.get("llm", "anthropic"))
+        if dry_run:
+            # In dry-run mode the LLM adapter is never actually called, so we
+            # tolerate missing dependencies (e.g. 'anthropic' SDK not installed).
+            try:
+                self._llm: LLMAdapter = self._build_llm(adapter_cfg.get("llm", "anthropic"))
+            except (ImportError, ValueError) as exc:
+                logger.warning(
+                    "LLM adapter unavailable in dry-run mode (%s) — continuing.", exc
+                )
+                self._llm = None  # type: ignore[assignment]
+        else:
+            self._llm = self._build_llm(adapter_cfg.get("llm", "anthropic"))
         self._vcs: Optional[VCSAdapter] = self._build_optional(  # type: ignore[assignment]
-            _VCS_ADAPTERS, adapter_cfg.get("vcs"), "VCS"
+            self._adapter_registry.get("vcs", {}), adapter_cfg.get("vcs"), "VCS"
         )
         self._notify: Optional[NotifyAdapter] = self._build_optional(  # type: ignore[assignment]
-            _NOTIFY_ADAPTERS, adapter_cfg.get("notify"), "notify"
+            self._adapter_registry.get("notify", {}), adapter_cfg.get("notify"), "notify"
-        )
-        self._default_runtime: RuntimeAdapter = self._build_runtime(
-            runtime_cfg.get("default", "openclaw")
-        )
-        self._coding_runtime: RuntimeAdapter = self._build_runtime(
-            runtime_cfg.get("coding_agent", "claude_code")
         )
+        # Runtime adapters are fully config-driven — one entry per string-valued
+        # key in the top-level ``runtime:`` section of team.yaml.
+        self._runtimes: dict[str, RuntimeAdapter] = self._build_runtimes(runtime_cfg)
 
         logger.info(
             "TeamRunner initialised: run_id=%s dry_run=%s", run_id, dry_run
@@ -198,7 +222,7 @@ class TeamRunner:
             return fh.read()
 
     def _build_llm(self, key: str) -> LLMAdapter:
-        cls = _load_adapter_class(key, _LLM_ADAPTERS, "LLM")
+        cls = _load_adapter_class(key, self._adapter_registry.get("llm", {}), "LLM")
         return cls(self._config)
 
     def _build_optional(
@@ -226,9 +250,25 @@ class TeamRunner:
             return None
 
     def _build_runtime(self, key: str) -> RuntimeAdapter:
-        cls = _load_adapter_class(key, _RUNTIME_ADAPTERS, "runtime")
+        cls = _load_adapter_class(key, self._adapter_registry.get("runtime", {}), "runtime")
         return cls(self._config)
 
+    def _build_runtimes(self, runtime_cfg: dict) -> dict[str, RuntimeAdapter]:
+        """
+        Build a name → RuntimeAdapter mapping from the ``runtime:`` config block.
+
+        Every key whose value is a string is treated as a runtime adapter name
+        and instantiated via ``_build_runtime``.  Non-string values (e.g.
+        ``native_teams: false``) are skipped so that boolean/numeric control
+        flags can coexist in the same config section.
+        """
+        runtimes: dict[str, RuntimeAdapter] = {}
+        for name, value in runtime_cfg.items():
+            if not isinstance(value, str):
+                continue
+            runtimes[name] = self._build_runtime(value)
+        return runtimes
+
     # ------------------------------------------------------------------
     # Role registry
     # ------------------------------------------------------------------
@@ -298,8 +338,9 @@ class TeamRunner:
 
         Routing
         -------
-        preferred_runtime == "coding_agent"  → coding runtime adapter
+        preferred_runtime == "standard" or empty/None → LLM adapter directly
-        preferred_runtime == "standard"      → LLM adapter directly
+        Otherwise → look up self._runtimes[preferred_runtime]; falls back to
+        self._runtimes["default"] and then to LLM if no runtime is found.
 
         Blackboard events emitted: spawned → completed | failed.
         """
@@ -320,10 +361,21 @@ class TeamRunner:
         )
 
         try:
-            if brief.preferred_runtime == "coding_agent":
+            pref = brief.preferred_runtime
-                result = self._dispatch_via_runtime(brief)
+            if not pref or pref == "standard":
-            else:
                 result = self._dispatch_via_llm(brief)
+            else:
+                runtime = self._runtimes.get(pref) or self._runtimes.get("default")
+                if runtime is None:
+                    logger.warning(
+                        "No runtime adapter found for %r (and no 'default') — "
+                        "falling back to LLM for brief %s",
+                        pref,
+                        brief.brief_id,
+                    )
+                    result = self._dispatch_via_llm(brief)
+                else:
+                    result = self._dispatch_via_runtime(brief, runtime)
 
             self._bb.update_brief_result(brief.brief_id, result)
             self._bb.log_event(
@@ -359,22 +411,22 @@ class TeamRunner:
         )
         return self._extract_json(raw)
 
-    def _dispatch_via_runtime(self, brief: TaskBrief) -> dict:
+    def _dispatch_via_runtime(self, brief: TaskBrief, runtime: RuntimeAdapter) -> dict:
-        """Spawn a coding agent via the runtime adapter and collect its result."""
+        """Spawn an agent via *runtime* and collect its result."""
         task_str = json.dumps(brief.to_dict(), indent=2)
         capability = _TIER_CAPABILITIES.get(brief.tier, "capable")
         timeout_s: int = brief.context.get("timeout_s", 300)
 
-        agent_id = self._coding_runtime.spawn(
+        agent_id = runtime.spawn(
             task=task_str,
             capability=capability,
             context=brief.context,
         )
         logger.info(
-            "Spawned coding agent %s for brief %s", agent_id, brief.brief_id
+            "Spawned runtime agent %s for brief %s", agent_id, brief.brief_id
         )
 
-        result = self._coding_runtime.get_result(agent_id, timeout_s=timeout_s)
+        result = runtime.get_result(agent_id, timeout_s=timeout_s)
 
         # Attempt to parse JSON from the agent's text output.
         if isinstance(result.get("output"), str) and result["output"].strip():
@@ -502,7 +554,9 @@ class TeamRunner:
         briefs: list[TaskBrief] = []
         for task in tasks:
             role = task.get("role", "default")
-            pref_runtime = task.get("preferred_runtime", "standard")
+            # T4 is the coding/implementation tier; default to coding_agent
+            # so implementers use Claude Code unless T3 explicitly overrides.
+            pref_runtime = task.get("preferred_runtime", "coding_agent")
             brief = parent.make_child_brief(
                 tier=4,
                 role=role,