Add hermes-atropos-environments skill (bundled)

Add comprehensive skill for building, testing, and debugging Hermes Agent
RL environments for Atropos training. Includes:

- SKILL.md: Full guide covering HermesAgentBaseEnv interface, required
  methods, config class, CLI modes (serve/process/evaluate), reward
  function patterns, common pitfalls, and minimum implementation checklist
- New 'Inference Setup' section: instructs the agent to always ask the
  user for their inference provider (OpenRouter + model choice, self-hosted
  VLLM endpoint, or other OpenAI-compatible API) before running tests
- references/agentresult-fields.md: AgentResult dataclass field reference
- references/atropos-base-env.md: Atropos BaseEnv API reference
- references/usage-patterns.md: Step-by-step patterns for process,
  evaluate, serve, and smoke test modes

Will be auto-synced to ~/.hermes/skills/ via skills_sync.

skills/mlops/training/hermes-atropos-environments/references/agentresult-fields.md

@@ -0,0 +1,59 @@
+# AgentResult Fields Reference
+
+`AgentResult` is defined in `environments/agent_loop.py` as a dataclass.
+
+## Fields
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `messages` | `List[Dict[str, Any]]` | Full conversation history in OpenAI message format |
+| `managed_state` | `Optional[Dict]` | ManagedServer.get_state() if Phase 2, else None |
+| `turns_used` | `int` | Number of LLM calls made during the loop |
+| `finished_naturally` | `bool` | True if model stopped calling tools on its own |
+| `reasoning_per_turn` | `List[Optional[str]]` | Extracted reasoning content per turn |
+| `tool_errors` | `List[ToolError]` | Tool errors encountered during the loop |
+
+## ToolError Fields
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `turn` | `int` | Which turn the error occurred |
+| `tool_name` | `str` | Name of the tool that failed |
+| `arguments` | `str` | Arguments passed to the tool |
+| `error` | `str` | Error message |
+| `tool_result` | `str` | The result returned to the model |
+
+## Extracting Data from Messages
+
+Messages follow OpenAI format. Common patterns:
+
+```python
+# Get final assistant response
+for msg in reversed(result.messages):
+    if msg.get("role") == "assistant" and msg.get("content"):
+        final_response = msg["content"]
+        break
+
+# Get all tool names used
+tools = []
+for msg in result.messages:
+    if msg.get("role") == "assistant" and msg.get("tool_calls"):
+        for tc in msg["tool_calls"]:
+            fn = tc.get("function", {}) if isinstance(tc, dict) else {}
+            tools.append(fn.get("name", ""))
+
+# Get tool results
+for msg in result.messages:
+    if msg.get("role") == "tool":
+        tool_output = msg.get("content", "")
+        call_id = msg.get("tool_call_id", "")
+```
+
+## Fields that DO NOT EXIST
+
+These are common mistakes — AgentResult does NOT have:
+- `final_response` — extract from messages
+- `tool_calls` — extract from messages  
+- `tools_used` — extract from messages
+- `output` — extract from messages
+- `response` — extract from messages