matlab-plan-grader-adoption
Use when an instructor asks for a MATLAB Grader assessment setup guide, adoption guide, pilot plan, course-specific rollout, QTI 3 sharing workflow, or recommended MATLAB Grader assessment-item-generation configuration based on a learning objective, course title, course description, module description, lab description, or assessment goal.
git clone --depth 1 https://github.com/matlab/agent-skills-playground /tmp/matlab-plan-grader-adoption && cp -r /tmp/matlab-plan-grader-adoption/demos/assessment-generation-for-matlab-grader/skills/matlab-plan-grader-adoption ~/.claude/skills/matlab-plan-grader-adoptionSKILL.md
# MATLAB Grader Instructor Setup Guide ## Purpose Generate a short instructor-facing setup guide for adopting the MATLAB Grader Assessment Item Generator skill in a course, module, lab, assessment sequence, or instructional-design workflow. Treat the user's provided objective, course description, assessment goal, or pilot request as the guide input. If the input is missing, ask for one sentence describing the course, module, learning objective, or assessment context before generating the guide. ## Input Handling Use the input to infer the best-fit setup context: - introductory MATLAB programming; - engineering computation or modeling; - data analysis or visualization lab; - object-oriented programming with MATLAB classes; - graded homework, quiz, lab, project, or exam preparation; - QTI 3 interchange, LMS review, or instructional-design sharing; - mixed or uncertain context. If multiple contexts fit, choose the primary context and add a short note about secondary considerations. Do not ask follow-up questions unless the input is too vague to identify an assessment goal. ## Guide Workflow 1. Restate the inferred learning objective or assessment goal. 2. Identify the best-fit assessment context and why it fits. 3. Recommend an assessment item type: Script, Function, Class, or Object usage. 4. Recommend assessment purpose: formative, summative, or both. When the context mapping has a purpose emphasis, use it. Otherwise default to summative for graded or unspecified use, and both when the module serves practice first with grading reuse later. 5. Provide an instructor-ready generation prompt for the `matlab-generate-grader-assessments` skill. 6. Define review gates for `description.txt`, `solution.m`, `template.m`, `function_call.m` when the recommended type is Function, and `tests.m`. 7. Define QTI 3 export and sharing guidance when portability is requested. 8. Propose a first pilot with one generated item, one review pass, and one revision loop. 9. Include a concise instructor checklist. Read [references/setup-guide-template.md](references/setup-guide-template.md) for context mapping, output format, prompt patterns, and adaptation rules. Read [references/research-summary.md](references/research-summary.md) when the user asks for research basis, evidence, rationale, literature mapping, or an instructor-facing explanation of the assessment design choices. ## Output Rules - Default to Markdown unless the user asks for another format. - Keep the guide practical enough for an instructor to use without extra setup. - Include concrete `matlab-generate-grader-assessments` prompts, not only advice. - Recommend QTI 3 only when the instructor asks for portability, LMS review, interchange, standards-based sharing, or instructional-design handoff. - State that QTI 3 preserves MATLAB Grader artifacts for interchange and does not make generic QTI runtimes execute MATLAB code. - Keep policies and institutional workflow language adjustable unless the user provides local requirements. - Include a brief research-basis section only when requested or when the guide is intended for departmental review, pilot approval, or assessment redesign.
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Use this skill when the user wants to author, design, scope, or refine an Agent Skill (a SKILL.md file). Trigger phrases include "build a new skill", "design an agent skill", "scope a SKILL.md", "how should I structure this skill", "write a skill for X", "my skill isn't working well", or any request to improve an existing SKILL.md. Walks the user through an empirical, test-first process — probe the agent for real failures, design only for genuine knowledge gaps, iterate against runnable examples, and verify across models.
Use this skill for any work involving a MATLAB Project (.prj file) — creating a new project, tracking files, managing the project path, configuring Simulink cache and code-generation folders, running project health checks, or writing build scripts that keep the project in sync with the file system. Trigger phrases include "set up a MATLAB project", "create a .prj", "track this file in the project", "project health check", "build script conventions". This skill is the generic foundation; domain-specific skills (e.g. `mbse-workflow`) build on it.
Use this skill for the architecture phases of an MBSE workflow in MATLAB, when writing idempotent buildXxx.m scripts that produce a three-layer RFLPV architecture (Functional, Logical, Physical) with interface dictionaries, stereotype profiles, allocation sets, and requirements Implement links. Trigger for defining stereotype properties, functional-to-logical / logical-to-physical allocation, mapping requirements to components via slreq Implement links, or running quantitative roll-up analysis on the architecture. Do NOT trigger for ad-hoc structural edits to an already-built System Composer model (adding one component, rewiring a port) — use `building-simulink-models` with `model_edit` for that. Works alongside the `system-composer` skill for detailed SC API patterns.
Use this skill for guided MBSE work in MATLAB — starting a new project, resuming work mid-workflow on an existing project, or answering orientation questions about how the MBSE skills fit together. Trigger when the user says they want to create, start, or set up a new MBSE project; work on a model-based systems engineering / RFLPV project; or asks which skill covers which phase. Walks through phases one at a time — propose → approve → generate → run → confirm. Use proactively whenever someone mentions starting or continuing an MBSE project.
Use this skill for all requirements-related work in a MATLAB MBSE project using the Requirements Toolbox (slreq). Covers creating and populating requirement sets, derivation links, test case requirements, verification coverage, reading and tracing links across requirement sets and models, checking link health, allocating requirements to components (Implement links), and building traceability reports. Trigger when the user asks about slreq API, slreqx files, slmx link files, outLinks/inLinks, traceability matrices, coverage analysis, broken links, or mapping requirements to architecture components. Use proactively for any requirements or traceability task.
Use this skill when authoring reusable, idempotent MATLAB scripts that build System Composer architecture models via the architecture-modeling API — `systemcomposer.createModel`, `addComponent`, `addPort`, `setInterface`, `connect(srcPort, dstPort)`, interface dictionaries (.sldd) with `addInterface`/`addElement`, profiles/stereotypes with `Profile.createProfile` and `addStereotype`, or `systemcomposer.allocation.createAllocationSet`. Also trigger when debugging these APIs (connections that don't appear, interfaces that don't resolve, profile save errors, `createAllocationSet` signature-mismatch errors). Do NOT trigger for ad-hoc structural edits to an already-built model (adding one SubSystem, rewiring a port) — use `building-simulink-models` with `model_edit` for that.
Optimize MATLAB code for better performance through vectorization, memory management, and profiling. Use when user requests optimization, mentions slow code, performance issues, speed improvements, or asks to make code faster or more efficient.