tylergarlick/abraxas/hermes

Claude Code and agent skill by tylergarlick/abraxas

Trust tier 3
  • community
Source check pending

Checking that the SKILL.md file is still in the repository.

Hermes — Multi-Agent Consensus & Divergence Tracker. Use this skill when multiple AI agents collaborate and you need to track consensus, detect divergence, or weight responses by track record. Track ledger of positions, detect convergence/divergence patterns. Commands: /hermes init, /hermes add, /hermes consensus, /hermes diverge, /hermes track-record, /hermes history, /hermes weight.

Install

npx vskill@latest install tylergarlick/abraxas/hermes

SKILL.md

Hermes — Multi-Agent Consensus & Divergence Tracker

Hermes (Greek: Ἑρμῆς, "the messenger") tracks consensus, disagreement, and information flow when multiple AI agents collaborate or when the same query is posed to multiple models. It maintains a ledger of positions, detects convergence/divergence patterns, and weights responses by historical track record.

Why Hermes?

When multiple AI agents collaborate, there's no built-in mechanism to know whether they agree, who to trust when they disagree, or how consensus forms over time. Hermes adds:

  • Crowd-sourced epistemic judgment — weighted by track record
  • Divergence detection — identifies when agents meaningfully disagree
  • Consensus tracking — shows how agreement evolves across interactions
  • Evidence trails — every collaborative conclusion has a provenance chain

Use Cases

  1. Multi-model queries: Pose the same question to multiple models and track agreement
  2. Collaborative problem-solving: Multiple agents work on the same problem, Hermes tracks convergence
  3. Consensus-building: Over turns, see how agent positions evolve toward or away from agreement
  4. Trust weighting: Weight responses by historical accuracy (track record)

Storage Location

`~/.abraxas/hermes/`

~/.abraxas/hermes/
├── ledger.json # Consensus/divergence ledger
├── track-records/ # Per-agent accuracy history
└── sessions/ # Session-specific consensus data

Command Suite

CommandDescription
/hermes init {session_id}Initialize a new Hermes consensus tracking session
/hermes add {agent_id} {position}Add an agent's position to the current session
/hermes consensusCompute consensus among tracked positions
/hermes divergeShow divergence detection results
/hermes track-record {agent_id}Show or update agent's historical track record
/hermes history {topic?}Show consensus history, optionally filtered by topic
/hermes weight {agent_id} {accuracy}Set/update agent's accuracy weight
/hermes statusShow current session status and participants

Core Concepts

Agent Position

An agent's stated position on a query or claim:

json
{
"agent_id": "model-ollama-llama3",
"timestamp": 1709999999,
"position": "The capital of France is Paris",
"confidence": "high",
"reasoning": "Geographic fact, well-established"
}
Consensus Types
  • Strong consensus: ≥80% agreement with high confidence
  • Weak consensus: 60-79% agreement
  • Divergence: <60% agreement or conflicting high-confidence positions
  • Unknown: Insufficient data for determination
Track Record

Each agent has a weighted track record:

json
{
"agent_id": "model-ollama-llama3",
"total_claims": 150,
"verified_correct": 135,
"accuracy": 0.90,
"last_updated": 1709999999
}
Weighted Consensus

Consensus weight = Σ(agent_accuracy × agent_position_agreement) / Σ(agent_accuracy)

This gives more weight to agents with better historical accuracy.

Usage Examples

Multi-Model Query
User: What is 2+2?
/hermes init math-001
/hermes add model-llama "4"
/hermes add model-mixtral "4"
/hermes add model-codellama "4"
/hermes consensus
→ Strong consensus: 3/3 agents agree (100%)
→ Weighted consensus: 0.93 (based on track records)
→ Position: "4"
Divergence Detection
User: What is the best programming language?
/hermes init lang-debate-001
/hermes add model-llama "Python is best for AI/ML"
/hermes add model-mixtral "Rust is best for safety"
/hermes add model-codellama "C++ is best for performance"
/hermes diverge
→ Divergence detected: 3 distinct positions
→ No consensus possible on subjective claim
→ Each agent's position noted with confidence
Track Record Weighting
/hermes track-record model-llama
→ model-llama: 90% accuracy (135/150 verified claims)
/hermes weight model-llama 0.85
→ Updated: model-llama accuracy weight set to 0.85

Integration with Janus

Hermes complements Janus by adding inter-agent perspective:

  • Janus labels [KNOWN]/[INFERRED]/[UNCERTAIN]/[UNKNOWN] — single-model epistemic state
  • Hermes tracks whether multiple models agree — multi-model epistemic state
  • Together: you see both "Is this true?" (Janus) and "Do others agree?" (Hermes)

Implementation

The core logic is in src/hermes.ts:

  • initSession(sessionId) — Create new consensus session
  • addPosition(agentId, position) — Add agent position
  • computeConsensus() — Calculate consensus among positions
  • detectDivergence() — Identify meaningful disagreement
  • getTrackRecord(agentId) — Retrieve agent's accuracy history
  • updateTrackRecord(agentId, correct) — Update after verification

See references/hermes-architecture.md for full technical details.

MCP tools

add_agent_position, compute_consensus, weight_record (Bun + TypeScript server, mcp/src/tools/hermes.ts; data in epistemic/consensus).

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
4
Repository forks
2
7-day trend score
8

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 4 Jul 2026, 4 months ago.

Works with

Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.

  • Claude Code
  • Cursor
  • GitHub Copilot
  • Windsurf
  • Codex
  • Gemini CLI
  • Cline
  • Amp
  • Roo Code
  • Goose
  • Continue
  • Kilo Code
  • Junie
  • Trae
  • OpenHands
  • Qwen Code
  • AI Agent
  • Tabnine Chat
  • Sourcegraph Cody
  • Amazon Q
  • Firebase Genkit
  • Sweep
  • Devin
  • Phind
  • Mentat
  • Claude Desktop
  • Aider
  • GPT Pilot
  • Plandex
  • bolt.new
  • v0
  • Replit Agent
  • Anse
  • TypingMind
  • BetterChatGPT
  • LibreChat
  • Warp AI
  • Pieces
  • Fig AI
Embed badge
vskill VERIFIED badge
[![vskill VERIFIED](https://verified-skill.com/api/v1/skills/tylergarlick/abraxas/hermes/badge)](https://verified-skill.com/skills/tylergarlick/abraxas/hermes)

Something wrong with this skill or its page? Tell us.