98cb570e96
All checks were successful
Deploy Skill to OCI / deploy (push) Successful in 19s
Makes the skill work on any laptop regardless of installed Python version or LLM harness, without per-command approval prompts or missing deps. - Makefile: auto-detect Python (venv > 3.12 > 3.11 > 3.10 > python3) and new `make venv` target that picks the best Python at creation time - .claude/settings.json: project-level Claude Code permissions (Write to examples/ and output/, common bash commands pre-authorized) - .codex/config.toml: Codex sandbox config with network_access=true, approval_policy=never, sandbox_mode=workspace-write — fixes `make venv` failing with "No matching distribution" in Codex - CLAUDE.md / AGENTS.md: document the `make venv` flow, drop all hardcoded python3.12 references in favor of make targets - CLAUDE.md: add Karpathy-style coding guidelines (think before coding, simplicity first, surgical changes, goal-driven execution) - .gitignore: add .venv/ Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
135 lines
5.1 KiB
Markdown
135 lines
5.1 KiB
Markdown
# OCI Deal Accelerator — Codex Setup
|
|
|
|
## Quick Start
|
|
|
|
### Option 1: Using Codex CLI (recommended)
|
|
|
|
```bash
|
|
# Navigate to the project root
|
|
cd oci-deal-accelerator
|
|
|
|
# One-time: create virtual environment with all dependencies
|
|
make venv
|
|
|
|
# Run Codex — it auto-discovers AGENTS.md, .agents/skills/, and .codex/config.toml
|
|
codex
|
|
|
|
# Or explicitly load the skill
|
|
codex --skill oci-deal-accelerator
|
|
```
|
|
|
|
Codex automatically reads:
|
|
- `AGENTS.md` at project root (project-level instructions)
|
|
- `.agents/skills/oci-deal-accelerator/SKILL.md` (the skill definition)
|
|
- `.codex/config.toml` (project sandbox + approval config — **enables network for pip**)
|
|
|
|
### Why `.codex/config.toml` matters
|
|
|
|
By default Codex CLI blocks network access and prompts before every command.
|
|
The committed `.codex/config.toml` pre-configures this project with:
|
|
|
|
- `approval_policy = "never"` — no per-command prompts
|
|
- `sandbox_mode = "workspace-write"` — agent can write in the repo
|
|
- `network_access = true` — `pip install` and `make venv` actually work
|
|
|
|
Without this file, `make venv` fails with `No matching distribution found for pyyaml` because PyPI is unreachable from the sandbox.
|
|
|
|
### Option 2: Using Codex App
|
|
|
|
1. Open the Codex app
|
|
2. Point it to this repository
|
|
3. The skill is auto-discovered from `.agents/skills/`
|
|
|
|
## File Structure (Codex-Specific)
|
|
|
|
```
|
|
├── AGENTS.md # Project instructions (Codex reads this)
|
|
├── .agents/
|
|
│ └── skills/
|
|
│ └── oci-deal-accelerator/
|
|
│ └── SKILL.md # Full skill definition (Codex skill format)
|
|
├── codex/
|
|
│ └── README.md # This file (setup guide)
|
|
├── kb/ # Knowledge Base (shared with all LLM targets)
|
|
├── tools/ # Python tooling (shared)
|
|
├── templates/ # ECAL phase templates (shared)
|
|
├── config/ # Configuration (shared)
|
|
└── examples/ # Example specs and outputs
|
|
```
|
|
|
|
## How It Works
|
|
|
|
### AGENTS.md vs SKILL.md
|
|
|
|
- **AGENTS.md** (project root): Codex reads this automatically when you open the project. It contains project structure, build commands, and conventions — equivalent to Claude Code's `CLAUDE.md`.
|
|
- **SKILL.md** (`.agents/skills/oci-deal-accelerator/`): The full skill definition with the welcome flow, ECAL workflow, output generation, guardrails, and multi-agent mode. Codex discovers this automatically from the `.agents/skills/` directory.
|
|
|
|
### AGENTS.override.md
|
|
|
|
If you need temporary overrides (e.g., focusing on a specific customer engagement), create an `AGENTS.override.md` at project root. It takes highest priority:
|
|
|
|
```markdown
|
|
# Override: Acme Corp Engagement
|
|
|
|
Focus on the Acme Corp engagement. The customer is migrating 5 Oracle 19c
|
|
databases from on-prem Exadata to OCI. Key constraints:
|
|
- Must use BYOL (ULA in place)
|
|
- PCI-DSS compliance required
|
|
- 4-hour RTO, 1-hour RPO
|
|
- Timeline: 12 weeks
|
|
```
|
|
|
|
## What the Skill Does
|
|
|
|
Takes unstructured customer discovery notes and produces:
|
|
- Architecture slide deck (.pptx) with Oracle FY26 branding
|
|
- Editable architecture diagram (.drawio) with official OCI styles
|
|
- Customer-facing PDF (branded, no internal KB refs)
|
|
- Cost estimates (PAYG vs BYOL breakdown)
|
|
- Well-Architected Framework scorecard
|
|
- Business case with TCO/ROI analysis
|
|
- ECAL readiness score (60 artefacts)
|
|
- Handover documents, go-live checklists, lessons learned
|
|
|
|
## 12 Capabilities
|
|
|
|
| # | Capability | Category |
|
|
|---|-----------|----------|
|
|
| 1 | Full proposal from discovery notes | Design & Propose |
|
|
| 2 | Generate architecture diagram | Design & Propose |
|
|
| 3 | Generate slide deck | Design & Propose |
|
|
| 4 | Cost estimate | Design & Propose |
|
|
| 5 | Well-Architected review | Validate & Check |
|
|
| 6 | Feature compatibility check | Validate & Check |
|
|
| 7 | Competitive comparison | Validate & Check |
|
|
| 8 | Business case builder | Strategy & Business |
|
|
| 9 | Search field findings | Knowledge Base |
|
|
| 10 | Find reference architecture | Knowledge Base |
|
|
| 11 | Report a field finding | Knowledge Base |
|
|
| 12 | ECAL readiness score | ECAL Governance |
|
|
|
|
## Multi-Agent Mode
|
|
|
|
When running in Codex with multiple agents enabled, the skill splits into:
|
|
|
|
- **Agent 1 (Architect)**: DEFINE + DESIGN phases — parses discovery, composes architecture
|
|
- **Agent 2 (Validator)**: WA validation — scores against 5 pillars
|
|
- **Agent 3 (Renderer)**: Output generation — deck, diagram, PDF, cost spreadsheet
|
|
|
|
Each agent reads the same KB but focuses on its phase.
|
|
|
|
## Requirements
|
|
|
|
- Python 3.8+
|
|
- Install dependencies: `pip install -r requirements.txt`
|
|
- Key packages: `pyyaml`, `python-pptx`, `reportlab` (for PDF)
|
|
|
|
## Also Works With
|
|
|
|
This skill is LLM-agnostic. The same KB and templates work with:
|
|
- **Claude Code** (Anthropic) — uses `SKILL.md` + `CLAUDE.md`
|
|
- **Codex** (OpenAI) — uses `AGENTS.md` + `.agents/skills/` (this setup)
|
|
- **ChatGPT** — paste SKILL.md as system prompt
|
|
- **Gemini Pro** — paste SKILL.md as system instruction
|
|
- Any LLM with tool/function calling support
|