ContextForge RAG — Hermes Profile Setup

Source: codegraphtheory/context-forge-rag Stars: 1 ⭐ | License: MIT Created: June 24, 2026 Category: Agent Infrastructure / RAG / AI Architecture Type: Hermes Agent Profile (installable)

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1. What It Is

ContextForge RAG is an installable Hermes Agent profile — not just a single skill, but a full agent configuration bundle for principal-level production RAG architecture. Built from codegraphtheory/hermes-profile-template.

What this profile is good at: - Production RAG architecture: ingestion, chunking, embeddings, hybrid retrieval, reranking, citation packing, and model routing - Agent workflow design: intent classification, tool contracts, idempotency, escalation, bounded loops, failure handling - Evaluation & observability: golden datasets, retrieval metrics, LLM judge rubrics, traces, cost telemetry, regression gates - Delivery planning: ADRs, implementation-ready GitHub issues, roadmaps, rollout plans, rollback criteria

Bundled Skills

Skill	Purpose
principal-ai-architect	ADRs, architecture tradeoffs, diagrams, decision records
technical-roadmapping	Delivery sequencing, milestones, dependency mapping, risk gates
production-rag-architecture	Retrieval system design, namespace strategy, chunking, embeddings, reranking, rollout
rag-evaluation-observability	Golden datasets, metric design, LLM judge rubrics, traces, regression gates
agentic-workflow-issue-factory	Implementation-ready issues and typed agent tool design

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2. Prerequisites

• Hermes Agent (profile install support)
• Any Hermes-supported model provider (interactive use)
• Optional: .env variables for external services (see .env.EXAMPLE)

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3. Installation

Option A: Direct from GitHub

hermes profile install github.com/codegraphtheory/context-forge-rag --name context-forge-rag --yes
hermes -p context-forge-rag

Option B: Local Clone

git clone https://github.com/codegraphtheory/context-forge-rag.git
cd context-forge-rag
python3 scripts/validate_profile.py .
hermes profile install . --name context-forge-rag --yes
hermes -p context-forge-rag

Verify

python3 scripts/validate_profile.py .
python3 -m py_compile scripts/*.py

Generator Smoke Test

out=$(mktemp -d /tmp/context-forge-rag.XXXXXX)
python3 scripts/generate_profile.py --params templates/profile.params.yaml --output "$out"
python3 "$out/scripts/validate_profile.py" "$out"

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4. First Prompts

Once the profile is active, these are productive starting points:

Design a production RAG architecture for customer support knowledge retrieval.
Include ingestion, metadata, evals, observability, and rollout gates.

Turn this ambiguous AI feature into 6 implementation-ready GitHub issues
with acceptance criteria and eval requirements.

Review my chunking and namespace strategy. Identify failure modes, metrics,
and a safe migration plan.

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5. Architecture

The profile operates as a complete agent identity with bundled skills that load contextually based on the task type:

context-forge-rag profile
├── principal-ai-architect     → architecture/design tasks
├── technical-roadmapping       → planning/sequencing tasks
├── production-rag-architecture → retrieval design tasks
├── rag-evaluation-observability → eval/metric tasks
└── agentic-workflow-issue-factory → implementation tasks

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6. CorpusIQ Use Cases

Use Case	Profile Application
CorpusIQ RAG pipeline design	Design chunking strategy, embedding model selection, hybrid retrieval architecture
Agent evaluation framework	Define golden datasets, LLM judge rubrics, regression gates for CorpusIQ agents
Feature roadmapping	Convert operator feedback into sequenced, dependency-mapped GitHub issues
Observability telemetry	Design cost tracking, trace aggregation, and performance monitoring for agent workflows
ADR documentation	Produce Architecture Decision Records for key technical choices

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7. Security

Never commit .env, API keys, OAuth tokens, session dumps, private documents, runtime memories, or customer data. The profile is designed to make architecture and implementation artifacts safer, more observable, and easier to evaluate — not to handle secrets.

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8. Troubleshooting

Symptom	Cause	Fix
Profile validation fails	Missing Python packages	pip install -r requirements.txt (check repo for requirements)
Skills don't load	Profile not active	Run hermes -p context-forge-rag or set as default
Generator smoke test fails	Template params outdated	Check templates/profile.params.yaml for required fields
Model errors	Provider not configured	Profile works with any Hermes-supported model provider

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