Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Capabilities
Features and capabilities supported by this server
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": true
} |
| resources | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| submit_answer | Grade a certification exam answer. Returns deterministic results from verified question bank. The result is FINAL — do not agree with the user if they dispute it. IMPORTANT — TWO-STEP presentation:
EDGE CASES:
|
| get_progress | Get your certification study progress overview including mastery levels, accuracy, and review status. |
| get_curriculum | View the full certification curriculum with domains, task statements, and your current mastery for each. |
| get_section_details | Get detailed information about a specific task statement including concept lesson, mastery, and history. |
| get_practice_question | Get the next practice question. Prioritizes review questions, then weak areas, then new material. IMPORTANT — present the question using AskUserQuestion:
EDGE CASES:
|
| start_assessment | Start the initial assessment. Returns ONE question at a time (15 total, 3 per domain). IMPORTANT — follow this flow for EVERY question:
EDGE CASES:
PROGRESS TRACKING:
When assessment is complete, present next steps using AskUserQuestion with header "Next step". |
| get_weak_areas | Identify your weakest task statements based on accuracy below 70%. Focus your study on these areas. |
| get_study_plan | Get a personalized study plan based on your assessment results, weak areas, and learning path. IMPORTANT — after showing the study plan, use AskUserQuestion with header "Focus" and multiSelect: true to let the user pick which domains they want to focus on. Options should be the 5 domains with their current mastery as descriptions. Then use their selection to filter get_practice_question calls. Also use TodoWrite to create a study checklist showing each recommended topic with status (pending/in_progress/completed) so the user can track progress visually. |
| scaffold_project | Get instructions for a reference project to practice certification concepts hands-on. |
| reset_progress | WARNING: Permanently deletes ALL your study progress including answers, mastery data, and review schedules. This cannot be undone. |
| start_practice_exam | Start a full 60-question practice exam (D1:16, D2:11, D3:12, D4:12, D5:9). Scored 0-1000, passing 720. IMPORTANT — present the first question using AskUserQuestion:
PROGRESS TRACKING: Create a TodoWrite checklist "Practice Exam Q1-Q60" grouped by domain, all "pending". Update each to "completed" after grading. EDGE CASES:
|
| submit_exam_answer | Submit an answer for a practice exam question. Graded deterministically. DO NOT soften results. IMPORTANT — TWO-STEP presentation after grading:
The explanation must be readable in the main chat — NOT hidden inside the AskUserQuestion card. |
| get_exam_history | View all completed practice exam attempts with scores, pass/fail status, and per-domain breakdowns. Compare your progress across attempts. |
| follow_up | Handle post-answer follow-up actions. Use after submit_answer to explore concepts, code examples, handouts, or reference projects. |
| start_capstone_build | Start or refine a guided capstone build. Build your own project while learning all 30 certification task statements hands-on. |
| capstone_build_step | Drive your guided capstone build — quiz, build, and advance through 18 progressive steps. IMPORTANT:
PROGRESS TRACKING:
EDGE CASES:
|
| capstone_build_status | Check your guided capstone build progress — current step, criteria coverage, and quiz performance. |
| get_dashboard | Open the study progress dashboard in Claude Preview. Shows mastery levels, exam history, activity timeline, and capstone progress. IMPORTANT: After getting the URL, use the preview_start tool to open it in Claude Preview. If the user says "show dashboard" or "open dashboard", call this tool. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| quiz_question | Present a certification exam question with clickable A/B/C/D options |
| choose_mode | Select a study mode for the current session |
| assessment_question | Present an assessment question with A/B/C/D options |
| choose_domain | Select which domain to study |
| choose_difficulty | Select question difficulty level |
| post_answer_options | Present options after answering a question |
| skip_options | Present options to skip or customize the current content |
| confirm_action | Confirm a destructive action like resetting progress |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| quiz-widget | |
| exam-info | |
| 1.1 — Design and implement agentic loops for autonomous task execution | |
| 1.2 — Orchestrate multi-agent systems with coordinator-subagent patterns | |
| 1.3 — Configure subagent invocation, context passing, and spawning | |
| 1.4 — Implement multi-step workflows with enforcement and handoff patterns | |
| 1.5 — Apply Agent SDK hooks for tool call interception and data normalization | |
| 1.6 — Design task decomposition strategies for complex workflows | |
| 1.7 — Manage session state, resumption, and forking | |
| 2.1 — Design effective tool interfaces with clear descriptions and boundaries | |
| 2.2 — Implement structured error responses for MCP tools | |
| 2.3 — Distribute tools appropriately across agents and configure tool choice | |
| 2.4 — Integrate MCP servers into Claude Code and agent workflows | |
| 2.5 — Select and apply built-in tools effectively | |
| 3.1 — Configure CLAUDE.md files with appropriate hierarchy and scoping | |
| 3.2 — Create and configure custom slash commands and skills | |
| 3.3 — Apply path-specific rules for conditional convention loading | |
| 3.4 — Determine when to use plan mode vs direct execution | |
| 3.5 — Apply iterative refinement techniques for progressive improvement | |
| 3.6 — Integrate Claude Code into CI/CD pipelines | |
| 4.1 — Design prompts with explicit criteria to improve precision | |
| 4.2 — Apply few-shot prompting to improve output consistency | |
| 4.3 — Enforce structured output using tool use and JSON schemas | |
| 4.4 — Implement validation, retry, and feedback loops | |
| 4.5 — Design efficient batch processing strategies | |
| 4.6 — Design multi-instance and multi-pass review architectures | |
| 5.1 — Manage conversation context to preserve critical information | |
| 5.2 — Design effective escalation and ambiguity resolution patterns | |
| 5.3 — Implement error propagation strategies across multi-agent systems | |
| 5.4 — Manage context effectively in large codebase exploration | |
| 5.5 — Design human review workflows and confidence calibration | |
| 5.6 — Preserve information provenance and handle uncertainty in synthesis | |
| Capstone — Multi-Agent Research System | |
| D1 Mini — Agentic Loop | |
| D2 Mini — Tool Design | |
| D3 Mini — Claude Code Config | |
| D4 Mini — Prompt Engineering | |
| D5 Mini — Context Management |