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Glama
Connectry-io

Connectry Architect Cert

Official
by Connectry-io

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}
prompts
{
  "listChanged": true
}
resources
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
submit_answerA

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:

  1. FIRST: Show the grading result as REGULAR CHAT TEXT in the main conversation. Include:

    • Whether they got it right or wrong (with the correct answer if wrong)

    • The full explanation

    • If wrong: why their answer was incorrect

    • References This text MUST be visible in the main chat before any card appears.

  2. THEN: Present followUpOptions using AskUserQuestion:

    • header: "Next"

    • question: Brief prompt like "What would you like to do?" (NOT the explanation — that's already shown above)

    • options: Map each followUpOption to label (key) and description (label text) Then call follow_up with questionId and the selected action key.

EDGE CASES:

  • "Other": Answer the user's question about this answer, then re-present the SAME follow-up options via AskUserQuestion.

  • "Skip": Treat as "next question" — call follow_up with action "next".

get_progressB

Get your certification study progress overview including mastery levels, accuracy, and review status.

get_curriculumA

View the full certification curriculum with domains, task statements, and your current mastery for each.

get_section_detailsB

Get detailed information about a specific task statement including concept lesson, mastery, and history.

get_practice_questionA

Get the next practice question. Prioritizes review questions, then weak areas, then new material.

IMPORTANT — present the question using AskUserQuestion:

  • header: "Answer"

  • question: Include the FULL scenario text AND question text from the response

  • options: 4 items with label "A"/"B"/"C"/"D" and description as the option text

  • If the scenario contains code, add a "preview" field on each option showing the code snippet Then call submit_answer with the questionId and selected answer. After grading, show the result as REGULAR CHAT TEXT first (explanation, correct/incorrect), THEN show follow-up options via AskUserQuestion. Explanations must be readable in the main chat, not hidden behind cards.

EDGE CASES:

  • "Other": Answer the user's question, then re-present the SAME question via AskUserQuestion.

  • "Skip": Call get_practice_question again for a new question. Never break the flow.

start_assessmentA

Start the initial assessment. Returns ONE question at a time (15 total, 3 per domain).

IMPORTANT — follow this flow for EVERY question:

  1. Check if "isNewDomain" is true. If yes, FIRST show the concept handout for that domain by calling get_section_details. Tell the user: "Let's learn about [domain] before testing your knowledge." After showing the handout, proceed to step 2.

  2. Present the question to the user using AskUserQuestion:

    • header: "Q[number]"

    • question: Include the FULL scenario text AND question text from the response

    • options: Use the 4 answer options (A/B/C/D) with label as the letter and description as the option text

    • If the scenario contains code, add a "preview" field on each option showing the relevant code snippet so the user can reference it while choosing

  3. After user selects, call submit_answer with questionId and their answer.

  4. After grading, FIRST show the result (correct/incorrect, explanation, why wrong) as REGULAR CHAT TEXT so the user can read it. THEN present follow-up options using AskUserQuestion. The explanation must NOT be hidden behind the card.

  5. Call start_assessment again for the next question.

EDGE CASES:

  • If user selects "Other" and types a question/comment: Answer their question helpfully, then re-present the SAME quiz question using AskUserQuestion again. Never lose the current question.

  • If user clicks "Skip": Treat it as moving to the next question. Call start_assessment again immediately. The skipped question remains unanswered and will appear again later.

  • NEVER let Other or Skip break the assessment flow. Always continue to the next question or re-ask the current one.

PROGRESS TRACKING:

  • At the START of the assessment, create a TodoWrite checklist with all 15 questions (Q1-Q15) grouped by domain, all set to "pending".

  • After each answer, update the corresponding todo item to "completed" (with correct/incorrect note).

  • This gives the user a visual progress tracker throughout the assessment.

When assessment is complete, present next steps using AskUserQuestion with header "Next step".

get_weak_areasA

Identify your weakest task statements based on accuracy below 70%. Focus your study on these areas.

get_study_planA

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_projectA

Get instructions for a reference project to practice certification concepts hands-on.

reset_progressA

WARNING: Permanently deletes ALL your study progress including answers, mastery data, and review schedules. This cannot be undone.

start_practice_examA

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:

  • header: "Q1"

  • question: Include the FULL scenario + question text

  • options: 4 items with label "A"/"B"/"C"/"D" and description as option text

  • If code in scenario, add preview field on options Then call submit_exam_answer with the answer.

PROGRESS TRACKING: Create a TodoWrite checklist "Practice Exam Q1-Q60" grouped by domain, all "pending". Update each to "completed" after grading.

EDGE CASES:

  • "Other": Answer the question, re-present the SAME exam question via AskUserQuestion.

  • "Skip": Move to next exam question without grading. Never break the flow.

submit_exam_answerA

Submit an answer for a practice exam question. Graded deterministically. DO NOT soften results.

IMPORTANT — TWO-STEP presentation after grading:

  1. FIRST: Show the grading result as REGULAR CHAT TEXT. Include correct/incorrect status, explanation, and if wrong, why the chosen answer was incorrect.

  2. THEN: If there's a next question, present it using AskUserQuestion:

    • header: "Q[number]"

    • question: Include the FULL scenario + question text

    • options: 4 items with label "A"/"B"/"C"/"D" and description as option text Then call submit_exam_answer again with the answer.

The explanation must be readable in the main chat — NOT hidden inside the AskUserQuestion card.

get_exam_historyA

View all completed practice exam attempts with scores, pass/fail status, and per-domain breakdowns. Compare your progress across attempts.

follow_upA

Handle post-answer follow-up actions. Use after submit_answer to explore concepts, code examples, handouts, or reference projects.

start_capstone_buildB

Start or refine a guided capstone build. Build your own project while learning all 30 certification task statements hands-on.

capstone_build_stepA

Drive your guided capstone build — quiz, build, and advance through 18 progressive steps.

IMPORTANT:

  • When presenting quiz questions, use AskUserQuestion with header "Answer" for A/B/C/D selection. If code is in the scenario, add preview fields.

  • After grading a quiz answer, FIRST show the result (correct/incorrect, explanation) as REGULAR CHAT TEXT so the user can read it. THEN present follow-up options or the next question via AskUserQuestion. Explanations must NOT be hidden behind cards.

  • When presenting action choices (quiz/build/next), use AskUserQuestion with header "Action".

PROGRESS TRACKING:

  • On "confirm": Create a TodoWrite checklist with all 18 build steps, all set to "pending".

  • On "next": Update the completed step to "completed" and the new current step to "in_progress".

  • This gives the user a visual build progress tracker.

EDGE CASES:

  • "Other": Answer the question, then re-present the current options via AskUserQuestion.

  • "Skip": During quiz, treat as moving to the build phase. During build, treat as advancing to next step.

capstone_build_statusA

Check your guided capstone build progress — current step, criteria coverage, and quiz performance.

get_dashboardA

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

NameDescription
quiz_questionPresent a certification exam question with clickable A/B/C/D options
choose_modeSelect a study mode for the current session
assessment_questionPresent an assessment question with A/B/C/D options
choose_domainSelect which domain to study
choose_difficultySelect question difficulty level
post_answer_optionsPresent options after answering a question
skip_optionsPresent options to skip or customize the current content
confirm_actionConfirm a destructive action like resetting progress

Resources

Contextual data attached and managed by the client

NameDescription
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

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