Why this set of changes:
- KB pricing was drifting silently — domain files (database.yaml,
storage.yaml, etc.) had prices 30-800% off the live Oracle API and
nobody read them. The skill was auditing as stale on every check
with no path to fix it.
- The skill itself violated Anthropic's spec (`name` field had
uppercase/spaces) and was over the 500-line guideline (647 lines),
hurting discovery and load performance.
- Welcome flow occasionally improvised the menu instead of reading
SKILL.md, missing options.
Pricing — single source of truth, fully automated:
- Extend tools/refresh_sku_catalog.py with --refresh-domain compute,
pulls shape-level prices from the Oracle public pricing API
(apexapps.oracle.com), preserves manual fields (notes, GPU specs,
free-tier annotations, estimation_helpers), recomputes derived
monthly values, and protects $0 free-tier prices from overwrite.
- Delete 12 redundant pricing/<domain>.yaml files. They duplicated
oci-sku-catalog.yaml with worse abstractions and were nobody's
source of truth (no tool consumed them).
- Migrate the genuinely valuable knowledge from those 12 files
(billing models, BYOL rules, free-tier rules, ECPU vs OCPU,
X11M elastic model, hyperscaler comparisons, service nuances)
into kb/field-knowledge/pricing-knowledge.yaml — non-numeric,
no refresh needed.
- Result: pricing freshness check goes from 13 stale files to 0.
KB freshness automation:
- Add tools/kb_freshness.py — wrapper around kb_linter.check_freshness()
with --check, --auto-refresh, --json, --quiet modes. Bridges stale
files to their refresh tools (SKU catalog, compute domain, arch
center). Wired into the welcome flow as a pre-flight banner that
asks the user before refreshing.
- Fix pre-existing kb_linter bug: it crashed on the 45 multi-doc
YAML files (frontmatter + body pattern) because it used safe_load
instead of safe_load_all. Freshness check was effectively dead.
- Standardize timestamp field: linter now accepts last_verified,
last_updated, and last_refreshed; refresh_arch_catalog writes
last_verified instead of last_refreshed.
- Add make freshness / make freshness-refresh targets.
Skill alignment with Anthropic Agent Skills best practices:
- Rename `name: OCI Deal Accelerator` to `oci-deal-accelerator`
to comply with the [a-z0-9-]{1,64} spec.
- Refactor SKILL.md from 674 to 445 lines via progressive disclosure:
extract WA review output format, ECAL readiness format, and output
conventions into docs/skill/*.md referenced from the main file.
- Add scripts/sync-skill.py + make sync-skill: source of truth is
root SKILL.md, .agents/skills/oci-deal-accelerator/SKILL.md is
auto-generated. make lint validates sync.
- Add evaluations/ with 3 manual baseline scenarios (welcome-flow,
full-proposal, wa-review) per the Anthropic best-practices guidance
to "build evaluations first."
Welcome flow hardening:
- Tighten CLAUDE.md to MANDATE reading SKILL.md before showing the
menu (no improvising), and document the freshness pre-flight check
with the ask-before-refresh user flow.
- Update SKILL.md welcome flow to instruct: parse kb_freshness JSON,
show banner with stale count + oldest file, prompt user to refresh
(only when an automated tool exists), fall back silently on errors.
Linter hygiene (zero remaining issues):
- Expand config/kb-tags.yaml taxonomy with features, operations,
metrics, limitations sections covering 31 previously-unknown tags
used in field findings (rac, ecpu, refreshable-clone, hnsw, etc.).
- Assign owners for kb/compatibility/, kb/competitive/,
kb/well-architected/ (Diego Cabrera as default until team grows);
kb/pricing/ marked as "Auto-refreshed" since it no longer needs
human ownership.
- kb_linter accepts top-level `date` as fallback for contributor
block; migrate FF-202603-008 from legacy `reported_by` to
contributor block.
- Result: linter goes from 45 issues to 0.
Other:
- Recompute estimation_helpers monthly values in compute.yaml after
the price refresh (they were derived from the old E5/A1 numbers).
- Add kb/README.md — contributor guide (directory map, frontmatter
spec, refresh tooling, review cadence).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
390 lines
18 KiB
Markdown
390 lines
18 KiB
Markdown
# OCI Deal Accelerator
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An AI-powered skill that acts as a **force multiplier for OCI Solutions Architects**. Feed it raw discovery notes from a customer call and get back a complete, defensible architecture proposal — ready to present.
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What normally takes an SA days of work (structuring notes, designing architecture, building decks, estimating costs, validating against Well-Architected) gets compressed into a single conversation. The skill doesn't just generate documents — it applies field-tested patterns, real pricing data, and lessons learned from actual OCI engagements to produce artifacts you can confidently put in front of a customer.
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**Fully aligned with Oracle's ECAL 3.1 framework** — covers all 9 steps (Ideate → Validate → Plan → Current → Future → Confirm → Adopt → Operate → Improve) with a catalog of 60 artefacts, engagement RACIs for 10 roles, and an ECAL Readiness Scorecard to track engagement completeness.
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### Key differentiators
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- **ECAL 3.1 native** — engagement RACI, artefact catalog, readiness scoring, and lessons learned per step baked into the workflow
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- **Field knowledge, beyond the docs** — built-in KB with real gotchas, workarounds, and sizing lessons from production OCI deployments
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- **Honest about trade-offs** — flags OCI limitations and competitive gaps instead of overselling
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- **Multi-cloud aware** — supports hybrid/multi-cloud diagrams (AWS, Azure, GCP icons) and considers options like ADB Multicloud before recommending full migration
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- **End-to-end coverage** — from discovery notes to go-live checklist, not just the architecture slide
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## What It Produces
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From unstructured input (meeting notes, emails, Slack threads), the skill generates:
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| Artifact | Format | ECAL Phase | ECAL Step |
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|---|---|---|---|
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| **Customer Profile** — strategic goals, Oracle footprint, industry analysis | YAML | Define | Ideate |
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| **Strategy Map** — goals → strategies → capabilities → enablers | YAML | Define | Ideate |
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| **Workload Profile** — structured discovery capture | YAML | Define | Ideate |
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| **Value Story** — business hypothesis linked to OCI outcomes | YAML | Define | Ideate |
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| **Business Case** — TCO, ROI, value drivers, risk assessment | .pptx | Define | Ideate |
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| **Joint Engagement Plan** — scope, resources, timeline | YAML | Define | Plan |
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| **Discovery Questionnaire** — structured IT landscape collection | YAML | Design | Current |
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| **Architecture Diagram** — official Oracle visual style, multi-cloud support | .drawio | Design | Future |
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| **Slide Deck** — 6-15 slides scaled to engagement complexity | .pptx | Design | Confirm |
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| **Customer PDF** — branded, no internal KB references | .pdf | Design | Confirm |
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| **Cost Estimate** — BYOL vs PAYG breakdown with assumptions | YAML | Design | Future |
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| **Well-Architected Scorecard** — 5-pillar automated validation | YAML | Design | Future |
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| **Operations Model** — day-2 monitoring, patching, incident response | YAML | Design | Future |
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| **ECAL Readiness Scorecard** — 60-artefact gap analysis per phase | Text | All | All |
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| **Delivery Artifacts** — handover, go-live checklist, success criteria | YAML | Deliver | Adopt |
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## Quick Start
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Feed `SKILL.md` as a system prompt to any LLM (Claude, GPT-4o, Gemini Pro). Then give it your discovery notes:
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```
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Here are my notes from the discovery call with Acme Corp:
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- 3 Oracle 19c databases on Exadata X8M on-prem, largest is 4TB OLTP
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- Using GoldenGate for replication to reporting DB
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- Need 99.95% availability, PCI compliance
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- Seasonal peaks 3x normal during Black Friday
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- Want to reduce costs, current Oracle licensing is $2M/year
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- Team has 2 Oracle DBAs, no cloud experience
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- CTO wants to move to cloud in 6 months
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- Comparing with AWS
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```
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The skill follows the ECAL workflow automatically: DEFINE (value story) → DESIGN (architecture) → DELIVER (handover).
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## Output Formats
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```
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deck ← default (.pptx)
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deck + drawio ← + editable diagram
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deck + doc ← + technical document
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deck + xlsx ← + cost spreadsheet
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deck + pdf ← + customer-facing PDF (branded, no internal refs)
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pdf ← customer PDF only
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bizcase ← business case deck for customer approval
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full ← everything (pptx + drawio + docx + xlsx + pdf)
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deliver ← handover + go-live checklist + success criteria
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```
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## Knowledge Base
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The KB is the moat — field experience, not documentation regurgitation.
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### Contributing to the KB
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Any SA can contribute knowledge to the skill. The KB lives in `kb/` as editable YAML files. Here's where each type of contribution goes:
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| What you want to contribute | Where it goes | How |
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| **Field caveat or workaround** | `kb/field-findings/tracker.yaml` | Menu option 11, or `python tools/findings_cli.py add` |
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| **Lesson learned** | `kb/field-knowledge/lessons-learned.yaml` | Edit YAML directly |
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| **Undocumented real-world limit** | `kb/field-knowledge/real-world-limits.yaml` | Edit YAML directly |
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| **Service caveat** | `kb/field-knowledge/gotchas.yaml` | Edit YAML directly |
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| **OCI service info** | `kb/services/<service>.yaml` | Create or edit the service YAML |
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| **Architecture pattern** | `kb/patterns/` | Add YAML following existing format |
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| **Architecture Center reference** | `kb/architecture-center/catalog.yaml` | `python tools/refresh_arch_catalog.py --url <url>` |
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| **Updated pricing** | `kb/pricing/oci-sku-catalog.yaml` (SKUs) or `kb/pricing/compute.yaml` (shapes) | `python tools/refresh_sku_catalog.py --refresh` (SKUs) or `--refresh-domain compute` (shapes). Both auto-pull from the Oracle public pricing API. |
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| **Feature compatibility** | `kb/compatibility/adb-feature-matrix.yaml` | Edit the matrix, mark `verified_in_field: true` |
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| **Competitive comparison** | `kb/competitive/` | Add or edit YAML with real pros AND cons |
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**Fastest path**: if you hit something in an engagement that another SA should know about, use menu option 11 (Report a field finding) — the skill walks you through the format and adds it to the tracker automatically.
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### OCI Pricing
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All pricing is auto-refreshed from the [Oracle public pricing API](https://apexapps.oracle.com/pls/apex/cetools/api/v1/products/?currencyCode=USD). No manually maintained pricing files.
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```
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kb/pricing/
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├── oci-sku-catalog.yaml # 200+ SKUs across 20 categories — single source of truth
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│ Refresh: python tools/refresh_sku_catalog.py --refresh
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└── compute.yaml # Shape-level estimation pricing (VMs, BM, GPU)
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Refresh: python tools/refresh_sku_catalog.py --refresh-domain compute
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kb/field-knowledge/pricing-knowledge.yaml
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# Stable pricing context: billing models, BYOL rules,
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free tiers, service nuances, hyperscaler comparisons.
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Non-numeric — no refresh needed.
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```
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### DBExpert Database Services Catalog
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35 Oracle Database services with full capabilities, multicloud availability (Azure/GCP/AWS locations), SLAs, MAA medals, compliance certifications, and certified Oracle applications. Sourced from the [Oracle DBExpert API](https://oracle-dbexpert.github.io/swagger/).
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```
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kb/services/dbexpert-catalog.yaml # 35 services, queryable by capability
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kb/services/dbexpert-api-reference.yaml # API endpoints and refresh procedure
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```
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### Architecture Center Catalog
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**123 Oracle Architecture Center reference architectures** (`kb/architecture-center/catalog.yaml`) covering Database@Azure/AWS/Google Cloud, networking, security, AI/ML, migration, HA/DR, and more.
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During **Phase 2 (DESIGN)**, the skill automatically matches the proposed architecture against the catalog:
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- **STRONG MATCH** (≥2 service + ≥1 tag) — cited in the Architecture Decisions slide
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- **MODERATE MATCH** (≥1 service + ≥2 tag) — referenced in the technical document
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```bash
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python tools/refresh_arch_catalog.py --whats-new # crawl What's New pages
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python tools/refresh_arch_catalog.py --url <url> # add a single entry
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python tools/refresh_arch_catalog.py --validate # validate catalog integrity
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```
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### Feature Compatibility Matrix
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Before recommending a deployment type, the skill checks `kb/compatibility/adb-feature-matrix.yaml` — a field-verified matrix of what works, what doesn't, and what has caveats the docs don't mention.
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```bash
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python tools/feature_matrix_cli.py check "Auto Scaling" adb_s 23ai
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python tools/feature_matrix_cli.py compare adb_s exacs 23ai
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python tools/feature_matrix_cli.py gaps dbcs_ee 23ai
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```
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### Field Findings Tracker
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Real issues, limitations, and workarounds encountered during customer engagements.
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```bash
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python tools/findings_cli.py search "maintenance window"
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python tools/findings_cli.py add
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python tools/findings_cli.py stats
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```
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### Competitive Positioning
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Honest AWS/Azure/GCP comparisons (`kb/competitive/`) that cover genuine advantages AND genuine gaps. No marketing — only field-verified facts.
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## ECAL Readiness Score
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Option 12 in the menu scores an engagement against the complete ECAL 3.1 framework:
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```
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══════════════════════════════════════════
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📊 ECAL READINESS SCORECARD
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══════════════════════════════════════════
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Customer: Acme Corp
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Current Phase: DESIGN
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Overall Readiness: 62% 🟡
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── DEFINE ──────────────────── 85% 🟢
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✅ Value Story
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✅ Workload Profile
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🟡 Customer Profile (missing Oracle footprint)
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❌ Strategy Map
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✅ Joint Engagement Plan
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── DESIGN ──────────────────── 55% 🟠
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✅ Future State Architecture
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✅ Cost Estimate
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🟡 Discovery Questionnaire (partial)
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❌ Operational RACI
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❌ Recovery Model
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...
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── TOP 5 GAPS ──
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1. ❌ Strategy Map — links solution to business goals
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2. ❌ Operational RACI — who runs what post go-live
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...
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══════════════════════════════════════════
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```
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The scorecard evaluates each of the **60 ECAL artefacts** from `kb/patterns/ecal-artefacts-catalog.yaml`, weighted by phase (DEFINE 25%, DESIGN 50%, DELIVER 25%). Readiness levels: 🟢 80%+ | 🟡 60-79% | 🟠 40-59% | 🔴 <40%.
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After scoring, the skill offers to generate missing artefacts, fix the top gap, or export the scorecard as a slide.
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## ECAL 3.1 Coverage
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The KB includes comprehensive ECAL 3.1 process knowledge:
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| KB File | What it covers |
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| `kb/patterns/ecal-artefacts-catalog.yaml` | All 60 ECAL artefacts with description, purpose, and skill support level |
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| `kb/patterns/engagement-raci.yaml` | RACI matrices for 10 roles across all 9 ECAL steps + lessons learned |
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| `kb/patterns/business-drivers.yaml` | 4-pillar framework (Strategic/Financial/BizOps/ITOps) + hypothesis families |
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| `kb/patterns/architecture-principles.yaml` | Design, Deployment, and Service principles from ECAL |
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| `kb/patterns/operational-raci.yaml` | 3 operational models (fully managed, co-managed, self-managed) |
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| `kb/patterns/service-tiering.yaml` | Platinum/Gold/Silver/Bronze service tier definitions |
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| `kb/patterns/environment-catalogue.yaml` | Environment templates per tier (prod, pre-prod, dev, DR) |
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| `templates/customer-profile.yaml` | Strategic customer profiling (goals, footprint, industry) |
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| `templates/strategy-map.yaml` | Goals → Strategies → Capabilities → Enablers mapping |
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| `templates/discovery-questionnaire.yaml` | Structured IT landscape collection with prioritization matrix |
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## Business Case Builder
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Option 8 in the menu generates a business case deck for customer internal approval:
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| Slide | Layout | Content |
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|-------|--------|---------|
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| Cover | Dark - Title_Pillar | Customer name + subtitle |
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| Executive Summary | Impact Statement | Bold 1-sentence opportunity |
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| Business Drivers | Multi Statement | 3 key drivers: Why now |
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| TCO Comparison | Blank + Table | Current vs OCI (3-5 year) |
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| ROI Headline | Blank + Metric | Big number (e.g., "2080% ROI") |
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| Value Drivers | Blank + Cards | 4 categories: Cost, Risk, Agility, Innovation |
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| Risk Assessment | Blank + 2-Column | Migration risks vs Do-nothing risks |
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| Roadmap | Blank + Timeline | Implementation phases |
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| Recommendation | Dark Impact | Clear ask with next steps |
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Uses the **Oracle FY26 official PowerPoint template** with Redwood design system.
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```bash
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python tools/oci_bizcase_gen.py --spec business-case.yaml --output business-case.pptx
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```
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## Welcome Flow
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When you start a conversation without discovery notes, the skill presents an interactive menu:
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```
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🏗️ OCI Deal Accelerator
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━━━━━━━━━━━━━━━━━━━━━━━
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Compresses your SA cycle from discovery to proposal — days to hours.
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Aligned with Oracle's ECAL framework (Define → Design → Deliver).
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What do you want to do?
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DESIGN & PROPOSE
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─────────────────
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1. 📋 Full proposal — notes → architecture + deck + diagram + costs
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2. 📐 Architecture diagram — YAML or description → .drawio
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3. 📊 Slide deck — architecture → .pptx
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4. 💰 Cost estimate — services + sizing → PAYG vs BYOL
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VALIDATE & CHECK
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─────────────────
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5. ✅ Well-Architected review — 5-pillar scoring + gaps
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6. 🔍 Feature compatibility — "does ADB-S support X?"
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7. 🆚 Competitive comparison — honest pros & cons vs AWS/Azure/GCP
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STRATEGY & BUSINESS
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─────────────────
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8. 💼 Business case — TCO, ROI, value drivers → exec deck
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KNOWLEDGE BASE
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─────────────────
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9. 🔎 Field findings — real issues + workarounds
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10. 📚 Reference architecture — Architecture Center lookup
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11. ➕ Report finding — log a gotcha from your engagement
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ECAL GOVERNANCE
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─────────────────
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12. 📊 ECAL readiness score — 60-artefact gap analysis
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━━━━━━━━━━━━━━━━━━━━━━━
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Pick a number, or just describe what you need.
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```
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If you paste discovery notes directly, the skill skips the menu and goes straight to the full proposal flow.
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## Tools
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```bash
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# Slide deck generation (technical proposal)
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python tools/oci_deck_gen.py --spec examples/proposal-spec.yaml --output proposal.pptx
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# Customer-facing PDF (branded, no internal KB refs)
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python tools/oci_pdf_gen.py --spec examples/proposal-spec.yaml --output proposal.pdf
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python tools/oci_pdf_gen.py --spec examples/proposal-spec.yaml --output proposal.pdf --diagram arch.png
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# Business case deck
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python tools/oci_bizcase_gen.py --spec business-case.yaml --output business-case.pptx
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# Architecture diagram
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python tools/oci_diagram_gen.py --spec examples/diagram-spec.yaml --output arch.drawio
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# Output orchestrator (multiple formats at once)
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python tools/oci_output.py --spec examples/proposal-spec.yaml --format full --output-dir output/
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# Architecture Center catalog
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python tools/refresh_arch_catalog.py --validate
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python tools/refresh_arch_catalog.py --whats-new
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# Feature compatibility
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python tools/feature_matrix_cli.py check "Auto Scaling" adb_s 23ai
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python tools/feature_matrix_cli.py compare adb_s exacs 23ai
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# Field findings
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python tools/findings_cli.py search "maintenance window"
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python tools/findings_cli.py stats
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# KB governance
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python tools/kb_cli.py health
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# WA validation
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python scripts/validate-architecture.py \
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--profile examples/sample-workload-profile.yaml \
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--architecture examples/sample-architecture.yaml \
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--output scorecard.yaml
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# Build automation
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make help
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```
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## Multi-LLM Support
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The skill is LLM-agnostic. The same KB and templates work across platforms:
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| Platform | How to use |
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|----------|-----------|
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| **Claude Code** | Uses `SKILL.md` + `CLAUDE.md` natively |
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| **OpenAI Codex** | Uses `AGENTS.md` + `.agents/skills/` (see below) |
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| **ChatGPT / GPT-4o** | Paste SKILL.md as system prompt |
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| **Gemini Pro** | Paste SKILL.md as system instruction |
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### OpenAI Codex Setup
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The repo is 100% compatible with [Codex CLI](https://github.com/openai/codex). Codex auto-discovers the skill on startup:
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```
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├── AGENTS.md # Project instructions (Codex reads automatically)
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├── .agents/skills/oci-deal-accelerator/
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│ └── SKILL.md # Full skill definition (YAML frontmatter + instructions)
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└── codex/
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└── README.md # Detailed setup guide
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```
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```bash
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# Just run Codex from the project root — auto-discovers everything
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cd oci-deal-accelerator
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codex
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# Or load the skill explicitly
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codex --skill oci-deal-accelerator
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```
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For temporary overrides (e.g., focusing on a specific customer), create `AGENTS.override.md` at the project root — it takes highest priority.
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Full setup details: [`codex/README.md`](codex/README.md)
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## Roadmap
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||
|
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### ECAL Completeness (see `docs/ecal-gaps-backlog.md` for full list)
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||
- Integration Catalog template — detailed integration mapping with data flows
|
||
- Cloud Operating Framework — 52-week operational plan (9 capability areas)
|
||
- OCI Operationalization Framework — 5-milestone deployment methodology
|
||
- POD (Pool of Databases) pattern — large-scale DB consolidation
|
||
- Banking/Financial compliance pattern — EBA/FCA/PRA mapped to OCI services
|
||
- ExaCC managed service pattern — complete ExaCC + ZDLRA/ZFS/OEM/OKV
|
||
|
||
### Platform
|
||
- Interactive what-if cost simulator (adjust ECPU/storage/commitment live)
|
||
- Automated migration complexity scoring from discovery notes
|
||
- Multi-region DR cost optimizer
|
||
- Engagement timeline generator (Gantt-style from Joint Engagement Plan)
|
||
- DBExpert API auto-refresh for database service catalog
|
||
- KB vectorizada en base de datos (RAG) — almacenar knowledge base en OCI 23ai con embeddings para busqueda semantica en lugar de lookup estatico por YAML
|
||
|
||
## Requirements
|
||
|
||
- Python 3.8+
|
||
- `pip install pyyaml python-pptx drawpyo requests beautifulsoup4 lxml reportlab`
|
||
- No OCI CLI or SDK needed (the skill designs, it doesn't deploy)
|
||
|
||
## License
|
||
|
||
Internal use. Not for distribution.
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