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* feat(gateway): skill-aware slash commands, paginated /commands, Telegram 100-cap Map active skills to Telegram's slash command menu so users can discover and invoke skills directly. Three changes: 1. Telegram menu now includes active skill commands alongside built-in commands, capped at 100 entries (Telegram Bot API limit). Overflow commands remain callable but hidden from the picker. Logged at startup when cap is hit. 2. New /commands [page] gateway command for paginated browsing of all commands + skills. /help now shows first 10 skill commands and points to /commands for the full list. 3. When a user types a slash command that matches a disabled or uninstalled skill, they get actionable guidance: - Disabled: 'Enable it with: hermes skills config' - Optional (not installed): 'Install with: hermes skills install official/<path>' Built on ideas from PR #3921 by @kshitijk4poor. * chore: move 21 niche skills to optional-skills Move specialized/niche skills from built-in (skills/) to optional (optional-skills/) to reduce the default skill count. Users can install them with: hermes skills install official/<category>/<name> Moved skills (21): - mlops: accelerate, chroma, faiss, flash-attention, hermes-atropos-environments, huggingface-tokenizers, instructor, lambda-labs, llava, nemo-curator, pinecone, pytorch-lightning, qdrant, saelens, simpo, slime, tensorrt-llm, torchtitan - research: domain-intel, duckduckgo-search - devops: inference-sh cli Built-in skills: 96 → 75 Optional skills: 22 → 43 * fix: only include repo built-in skills in Telegram menu, not user-installed User-installed skills (from hub or manually added) stay accessible via /skills and by typing the command directly, but don't get registered in the Telegram slash command picker. Only skills whose SKILL.md is under the repo's skills/ directory are included in the menu. This keeps the Telegram menu focused on the curated built-in set while user-installed skills remain discoverable through /skills and /commands.
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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:
# 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 messagestool_calls— extract from messagestools_used— extract from messagesoutput— extract from messagesresponse— extract from messages