hermes-agent/optional-skills/mlops/hermes-atropos-environments/references/agentresult-fields.md
Teknium 5ceed021dc
feat(gateway): skill-aware slash commands, paginated /commands, Telegram 100-cap (#3934)
* 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.
2026-03-30 10:57:30 -07:00

2 KiB

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 messages
  • tool_calls — extract from messages
  • tools_used — extract from messages
  • output — extract from messages
  • response — extract from messages