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How I Scored 910/1000 on CCAF Claude Certification and Open-Sourced My Last Cheat Sheet

A developer scored 910/1000 on the Claude Certified Architect Foundations (CCAF) exam and open-sourced their study notes on GitHub. The repository distills 30 exam tasks across five domains into concept maps, trap taxonomies, and an anti-patterns catalog to help others prepare.

read4 min views1 publishedJul 28, 2026

I passed Claude Certified Architect Foundations (CCAF) with 910/1000 on 15 July 2026, and I'm the first at my company to finish it. I open-sourced the study notes I built: ** github.com/ahmdhsn-dev/ccaf-study-guide**.

CCAF is scenario-heavy: you pick the right architecture when an agent forgets context, a generic tool keeps misfiring, or a customer escalation lands mid-process. The official guide covers all of it, but it's dense. The repo distills 30 exam tasks across 5 domains into two complementary views: what to do (patterns and traps) and what not to do (anti-patterns).

What's inside: a one-page concept map, a trap taxonomy (why wrong answers sound right), and an anti-patterns catalog that maps every "avoid / do not / instead of" warning from the official guide. If a distractor sounds plausible, check the traps first; if it sounds like a shortcut the guide rejects, check the anti-patterns.

Use it as your last cheat sheet, not your textbook. Take a mock first to see where you stand, then study the official guide and use the repo to close the gaps.

Full workflow: study/README.md

Building with the Claude API → Claude Code in Action → Introduction to Agent Skills → Introduction to MCP

I completed all four with hands-on labs in May 2026. Production work with skills, MCP servers, and tool orchestration helped, but the exam tests guide patterns, not how your repo is wired.

Step Doc What you get
1

Domain weights: Agentic Architecture (27%) · Tool Design & MCP (18%) · Claude Code Config (20%) · Prompt & Structured Output (20%) · Context & Reliability (15%). See the concept map for task breakdown.

Take the CyberSkill mock first (closest to the real exam), then the Certification Guide short mock. My first CyberSkill run scored 850/1000; after mapping misses to the guide and retaking, I was consistently 950+ before booking. For every miss, map it to the trap taxonomy, cross-check the anti-patterns catalog, re-read the matching section in the official guide, and repeat until you're consistently at 900+ (I booked at 950+).

Mocks are your prerequisite gate, not an arbitrary iteration cap. You won't feel ready. The exam has stop_reason: end_turn

before you do, and that's normal.

Nine misses on my first CyberSkill run; these three patterns accounted for most of them (full mapping in the cheat sheet below):

analyze_document

with an enum modeHigh-yield patterns from mock exams. Full taxonomy: 02-mock-exam-trap-guide.md.

Context filling up (multi-issue)     → 5.1 Summarize resolved; active thread full
Generic tool, inconsistent output    → 2.1 Split typed tools
Messy source formats                 → 4.3 Schema + normalization in prompt
Function behind wrappers             → 2.5 List aliases → grep each
Agent forgets mid-conversation       → 5.1 Pass full messages array
Unknown bug path                     → 1.6 Adaptive investigation
Long code exploration (30+ min)      → 5.4 Scratchpad file
Mid-process escalation               → 1.4 Structured handoff brief
Angry + no context                   → 5.2 Acknowledge + one question
Identity multi-match                 → 5.2 Ask identifiers, never guess
Trap Sounds like... Guide-preferred
Sounds enterprise Structured data layer, reference IDs Progressive summarization
Sounds efficient Re-fetch via MCP, parallel workers Trim/summarize context
Sounds smart Confidence threshold, routing classifier Explicit criteria; programmatic gates
Sounds helpful Immediate escalation, unauthorized retry Calibrated: brief, one question, or resolve
Sounds thorough Plan everything first Adaptive evidence-driven steps
Sounds simple Better description on generic tool Split tools + typed schemas
Sounds pragmatic Post-processing normalization Canonical format at extraction

From 03-anti-patterns-catalog.md:

1. Heuristic customer selection on multi-match: ask for email, phone, or order ID; never confidence-threshold auto-pick (Task 5.2).

2. Sliding window drops resolved threads: progressive summarization on resolved issues; keep active thread full (Task 5.1).

3. Generic analyze_document + free-text mode: split into

extract_data_points

, summarize_content

, etc. (Task 2.1).4. Batch API for pre-merge blocking checks: sync Messages API for blocking; Batch for overnight audits (Task 4.5).

5. Giving synthesis agent web search tools: scope to verify_fact

; route new lookups through coordinator (Task 2.3).

Topic Exam (guide) Production (2026)
Structured output
tool_use + JSON schema
Also output_config.format ; prefill removed on new models
Batch tool use No multi-turn in one request Server tools + _turn ; client MCP loops still multi-request
/memory
Diagnostic command (in scope) Plus expanded CLAUDE.md / rules / skills ecosystem

Full breakdown: 04-api-and-product-faq.md

** github.com/ahmdhsn-dev/ccaf-study-guide**. MIT licensed, unofficial, not affiliated with Anthropic.

Community links and extra mocks: resources/links.md

Disclaimer: Based on the exam taken 15 July 2026. Unofficial, not affiliated with Anthropic. Verify latest exam requirements before you sit.

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