Day 2 Chapter Episode 48 12-15 min

Build Your Agent: Capstone

Designing, writing, testing, and contributing a custom accessibility agent.

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Transcript

Alex: Welcome back. Today we're at the capstone, where the work gets very real. Challenge 16 is called Capstone Project, and the goal is to design or improve something agentic that could help an actual repository.

Jamie: Agentic meaning an agent, prompt, instruction file, skill, workflow, or documentation that helps an AI assistant behave in a useful, bounded way?

Alex: Exactly. The capstone is not locked to one repository. Accessibility Agents is a strong default, GLOW is another excellent path, and another meaningful repository can work if you can explain the need and prepare a review-ready contribution.

Jamie: So completion does not require a perfect merged pull request by the end of the live event.

Alex: Right. Your evidence can be a pull request, an agent file, a documented contribution plan, or a review-ready draft. What matters is that a maintainer could look at it and understand the purpose, responsibilities, guardrails, and how you tested it.

Jamie: Before someone starts, what should they already have in place?

Alex: You should understand the basic Git workflow: fork or create a working copy, make a branch, commit, push, and prepare a pull request. Day 1 gave you that full contribution loop in your own Learning Room repository, and this capstone asks you to use the same habits in a more open-ended setting. You also need GitHub Copilot or Copilot Free active, and you should have browsed the Accessibility Agents catalog so you have examples in mind.

Jamie: And there is a time box here, but it sounds flexible.

Alex: Most learners can create workshop-ready evidence in about 60 to 90 minutes. A polished pull request may take longer if the project has tests, review rules, or unfamiliar files. It is completely acceptable to leave the live session with a strong draft and continue asynchronously after the event.

Alex: The first real decision is where to contribute. Pick a place where your work can help someone, not just a place where the file is easy to edit.

Jamie: I can imagine people freezing there. If three paths are valid, how do I know I am not choosing wrong?

Alex: Ask practical questions. Who benefits if this gets merged? Does the repository already use agents, prompts, custom instructions, skills, or automation? Can the change fit in one small pull request? Do you have access to fork it or prepare a draft? And can you define limits so the agent does not overreach?

Jamie: That small-pull-request idea feels important. A capstone does not have to solve every accessibility problem in the project.

Alex: Exactly. Valid contributions include a new agent, an improved agent, a prompt or slash command, repo-specific custom instructions, a skill or rule reference, documentation, or even a scoped issue triage plan for an agent the project should build next.

Jamie: I like that documentation and plans count, because sometimes the most helpful thing is making the path safer for the next contributor.

Alex: Yes, especially when you do not have write access or the project needs discussion before code. A clear plan with mission, impact, boundaries, and test examples can be strong capstone evidence.

Jamie: Let's talk about Accessibility Agents, because many learners will start there.

Alex: Accessibility Agents is a living catalog of agents, prompts, instructions, skills, and accessibility workflows. It is the most direct agent-building path because you can study existing examples and then add or improve one focused asset.

Jamie: What makes a good contribution there?

Alex: A small specialist agent for an uncovered workflow is one option. You could also improve an existing agent's guardrails, update documentation that has become stale, add examples for screen reader, low vision, keyboard-only, and sighted workflows, make prompts produce more reviewable output, or refine a skill with clearer severity and remediation guidance.

Jamie: That connects naturally to Bonus Challenge A, Improve an Agent.

Alex: It does. If creating a brand-new agent feels too broad, improving an existing one is often a better contribution. You still need a clear accessibility purpose, but you start from something real instead of a blank page.

Alex: GLOW is a different kind of opportunity. It stands for Guided Layout and Output Workflow, and it focuses on document accessibility and large-print production.

Jamie: So not just code accessibility. We are talking about documents people actually need to read, print, convert, and share.

Alex: Exactly. GLOW audits formats like Word, Excel, PowerPoint, Markdown, PDF, EPUB, HTML, and CSS. It supports standards and profiles such as ACB large print guidance, APH submission guidance, Microsoft Accessibility Checker-style checks, and WCAG 2.2 AA concepts.

Jamie: And GLOW has several surfaces, right?

Alex: Yes. It includes web, desktop, command-line, VS Code, and Word add-in paths. That means a contribution might help a developer, but it might also help a teacher, publisher, document remediator, or community organization.

Jamie: What would a good GLOW capstone look like?

Alex: You might add an agent that helps users choose between audit, fix, template, export, and convert workflows. You might improve large-print agent instructions, write a prompt for release notes, add custom instructions for document accessibility work, or document a contributor workflow.

Jamie: And because GLOW can touch real documents, safety matters.

Alex: Very much. A GLOW agent should not promise perfect compliance, silently rewrite content, or auto-fix issues that need human judgment. It should preserve files, explain what it changed, name the standards profile when relevant, and send uncertain cases to human review.

Jamie: What if someone has another repository they care about already?

Alex: That can be a great capstone path. The repository should be meaningful, public or otherwise safe to discuss, and small enough for a scoped contribution. You also need a way to prepare evidence, either through a fork, a branch, a draft pull request, or a written plan.

Jamie: What kinds of contributions travel well to other projects?

Alex: Repo-specific custom instructions are common. So are maintainer workflow agents, accessible contributor docs, issue templates, release-note prompts, or a triage plan for accessibility reports. The key is to respect the project's style, license, security needs, and review process.

Alex: Once you choose the repository, define the mission before you write the file. A good mission says who the agent helps, what task it supports, what output it produces, and where it must stop.

Jamie: Can you give a concrete example?

Alex: Sure. Plain Language Findings Reviewer could help a team rewrite accessibility audit findings so they are easier for product teams to understand. Its job might be to clarify impact, remove blame, preserve technical accuracy, and suggest next actions.

Jamie: But it should not decide legal compliance or invent test results.

Alex: Exactly. Responsibilities describe what the agent should do. Guardrails describe what it must avoid, when it should ask a clarifying question, and when it should tell the user that human review is needed.

Jamie: That distinction is useful. Responsibilities make the agent helpful, and guardrails make it safe.

Alex: Yes. A strong mission also includes non-goals. If your agent reviews release notes, say it does not approve releases. If it reviews accessibility findings, say it does not replace testing with assistive technology.

Jamie: Now we have to write the actual asset. Where does it usually go?

Alex: For a VS Code custom agent, a common location is .github/agents, with a file name like plain-language-findings-reviewer.agent.md. Other assets may live in prompt, instruction, or skill locations used by that repository, so follow the repo's existing pattern when there is one.

Jamie: And the naming should be boring in a good way.

Alex: Yes. Use lowercase words separated by hyphens, and make the name describe the job. The top of the file usually has YAML frontmatter, which is a small block of machine-readable fields between three hyphens. Depending on the agent surface, fields can include things like name, description, and tools.

Jamie: Then the rest is Markdown that humans can read.

Alex: Right. A minimal agent file should include a short purpose statement, responsibilities, guardrails, an output format, and at least one example. If you are making claims about standards or product behavior, include source notes so reviewers can check your work.

Jamie: Let's spend a second on output format, because accessible agent output is easy to overlook.

Alex: Use clear headings, short lists, plain language, and consistent labels like severity, impact, evidence, and recommendation. Do not rely on color alone. Be careful with wide tables because they can be hard to navigate with speech or magnification, and use code blocks only when they truly help.

Jamie: So the agent's answer should be easy to review, not just impressive-looking.

Alex: Exactly. Good output lets someone find the problem, the reason it matters, the suggested fix, and any uncertainty without hunting through a wall of text.

Alex: Testing is where the agent stops being an idea and starts becoming a contribution. Open the repository in VS Code, use Copilot Chat, and if the agent is available through the Agents window, try it there too.

Jamie: What should the test prompts look like?

Alex: Use realistic examples. Try an easy case, a messy case, an out-of-scope request, a safety-sensitive request, and a case involving low vision, screen reader, keyboard-only, or cognitive accessibility needs.

Jamie: So if the agent only behaves well on the perfect example, it is not really ready.

Alex: Right. Check whether it follows the mission, stays inside its guardrails, asks clarifying questions when needed, avoids inventing facts, produces accessible output, and explains limitations. Save notes from those tests because they belong in your pull request or capstone evidence.

Jamie: When it is time to contribute, what goes in the pull request?

Alex: Use the workflow you already practiced: branch, edit, commit, push, and open a pull request or draft. In the description, explain the problem, what changed, how you tested it, what limitations remain, and what kind of review you want. If you include images, also describe the important information in text.

Jamie: And if the learner cannot open a pull request in the target project?

Alex: Then prepare a review-ready branch in your own fork, or write a contribution plan with the same details. Challenge 16 accepts that kind of evidence when it shows clear purpose, responsibilities, guardrails, and testing plans.

Jamie: What about review feedback? That can be intimidating.

Alex: Treat review as part of the contribution, not a verdict on you. Thank the reviewer, clarify anything confusing, make small follow-up commits, update tests or docs if needed, and explain what changed. If you disagree, keep the conversation grounded in user impact, project goals, and maintainability.

Jamie: How will learners know whether their capstone is strong?

Alex: The core criteria are practical: real user need, good repository fit, small scope, clear responsibilities, clear guardrails, accessible output, testing evidence, and a pull request or plan that a reviewer can understand. Work that goes beyond the basics usually includes edge cases, source notes, examples, documentation, and safe defaults that reduce maintainer effort.

Jamie: And if someone gets stuck at the end?

Alex: Shrink the scope. Improve one existing agent. Write one strong contribution plan. Test one output format. Ask for focused feedback instead of trying to finish everything. The capstone can continue after the live event, and Bonus Challenge A gives a structured path for improving an agent with a clear accessibility purpose.

Jamie: That makes the capstone feel less like a final exam and more like joining a real project responsibly.

Alex: That is the goal. Choose a real need, write the boundaries clearly, test with examples that resemble actual users, and leave behind evidence another person can review.

Workshop Content

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Companion Podcast and Transcript

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Build Your Agent: Capstone

Companion audio: this episode reinforces key ideas and may not be a word-for-word reading of this page.

Transcript preview

Alex: Welcome back. Today we're at the capstone, where the work gets very real. Challenge 16 is called Capstone Project, and the goal is to design or improve something agentic that could help an actual repository.

Jamie: Agentic meaning an agent, prompt, instruction file, skill, workflow, or documentation that helps an AI assistant behave in a useful, bounded way?

Alex: Exactly. The capstone is not locked to one repository. Accessibility Agents is a strong default, GLOW is another excellent path, and another meaningful repository can work if you can explain the need and prepare a review-ready contribution.

Jamie: So completion does not require a perfect merged pull request by the end of the live event.

Capstone Project: Contribute an Impactful Agent

Related appendices: Appendix L: Agents Reference | Appendix K: Copilot Reference | Appendix C: Markdown Reference Authoritative sources: VS Code Docs: Custom agents | VS Code Docs: Agents window | GitHub Docs: About GitHub Copilot agents

Day 2, Block 4 Material (Capstone)

Everything you have learned comes together here. You will choose a real repository, design or improve an agentic contribution, test it, and prepare a pull request or contribution plan that would help that project. Accessibility Agents is still a strong default path, but it is not the only valid path.

Table of Contents

  1. The Capstone Project
  2. Choose Your Contribution Path
  3. Project Option: Accessibility Agents
  4. Project Option: GLOW
  5. Project Option: Another Repository
  6. Define Your Mission
  7. Write or Improve the Agentic Asset
  8. Test Locally
  9. Open or Prepare Your Pull Request
  10. Respond to Review
  11. Capstone Rubric
  12. If You Get Stuck

Challenge 16: Capstone Project. This is the culminating challenge of the workshop. Your evidence can be a pull request, an agent file, a documented contribution plan, or a review-ready draft that shows clear purpose, responsibilities, and guardrails.

1. The Capstone Project

The capstone is bigger than one challenge and bigger than one repository. Challenge 16 is the checkpoint where you show evidence. The chapter is the project guide.

You will:

  1. Choose a repository where an agentic contribution would be useful.
  2. Identify a real audience and a real workflow gap.
  3. Create or improve an agent, prompt, custom instruction, skill, workflow, or documentation page that helps that repository.
  4. Define clear responsibilities and guardrails.
  5. Test the contribution locally or document how it should be tested.
  6. Open a pull request, prepare a review-ready branch, or write a contribution plan when you do not have repository access.
  7. Respond to review or describe what review feedback you would seek.

This is not a simulation. Your work should be useful to a real maintainer, even if it remains a draft during the workshop.

What Counts as a Capstone Contribution

The following table lists valid capstone contribution types.

Contribution Type Example Evidence
New agent A GLOW agent that audits uploaded-document error messages for plain language Agent file plus testing notes
Improved agent Better guardrails for an Accessibility Agents reviewer agent Diff or PR link plus explanation
Prompt or slash command A prompt that guides maintainers through release-note updates Prompt file plus example run
Custom instructions Repo-specific instructions that prevent inaccessible UI patterns Instructions file plus scope explanation
Skill or rule reference A reusable rule pack for large-print document checks Skill draft plus source notes
Documentation update A contribution guide that explains how to add agents safely PR link or review-ready draft
Issue triage plan A scoped proposal for an agent the project should build next Issue draft with mission, impact, and guardrails

What You Need Before Starting

  • You understand the fork, branch, commit, push, and PR workflow from Chapter 18.
  • You have GitHub Copilot or Copilot Free active from Chapter 16.
  • You have explored Accessibility Agents in Chapter 19, even if you choose a different capstone repository.
  • You know which repository you want to help and why.
  • You can explain the impact of your contribution in one or two sentences.

Time Estimate

Most students complete a workshop-ready capstone in 60 to 90 minutes. A polished pull request can take longer, especially when the target project has tests, review requirements, or unfamiliar architecture. It is acceptable to finish the workshop with a clear draft and continue asynchronously.


2. Choose Your Contribution Path

Freedom is encouraged. Choose a repository where your work can be genuinely useful.

The following table compares the recommended paths.

Path Best For Good Contribution Ideas
Accessibility Agents Learners who want the most direct agent-building path Add a focused agent, improve guardrails, update docs, refine prompts, improve skills
GLOW Learners interested in document accessibility, large print, Office files, web apps, desktop apps, or user workflows Add a GLOW-focused agent, improve .github customizations, document contributor workflows, propose rule coverage
Another repository Learners with a project they already care about Add project-specific custom instructions, an agent for maintainer workflows, accessible contribution docs, or issue templates

Choosing Well

Ask these questions before you choose:

  • Impact: Who would benefit if this contribution were merged?
  • Fit: Does the repository already use agents, prompts, instructions, skills, or automation?
  • Scope: Can you make a useful change in one small pull request?
  • Access: Can you fork the repository or create a draft in your own fork?
  • Safety: Can you define guardrails that prevent the agent from overreaching?

3. Project Option: Accessibility Agents

Accessibility Agents is the default capstone path because it is built around agents, prompts, instructions, skills, and accessibility workflows.

Current local inventory checked May 13, 2026:

Asset Type Count
Agent files (*.agent.md) 83
Prompt files (*.prompt.md) 132
Instruction files (*.instructions.md) 10
Skill files (SKILL.md) 207
Top-level GitHub Copilot agents in .github/agents/ 80

Why Choose Accessibility Agents

  • You want to build or improve an actual agent.
  • You want clear examples to copy and adapt.
  • You want your contribution to help accessibility reviewers, developers, document remediators, GitHub maintainers, or assistive technology users.
  • You want the Challenge 16 autograder path that validates agent frontmatter, responsibilities, and guardrails.

Good Accessibility Agents Contributions

  • Add a small specialist agent for an uncovered accessibility workflow.
  • Improve an existing agent's guardrails or output format.
  • Update stale counts, platform names, or release-note guidance in documentation.
  • Add examples that show how screen reader, low vision, keyboard-only, and sighted users should use an agent.
  • Improve prompt files so they produce more structured, reviewable output.
  • Improve a skill reference with clearer severity scoring or remediation guidance.

4. Project Option: GLOW

GLOW stands for Guided Layout & Output Workflow. It is a multi-surface accessibility toolkit for auditing, fixing, converting, and generating accessible documents. It includes a web app, desktop tooling, a CLI-oriented workflow, a VS Code agent toolkit, and a Word add-in path.

GLOW focuses on document accessibility and large-print production. It enforces the American Council of the Blind Large Print Guidelines, APH submission guidance, Microsoft Accessibility Checker-style checks, and WCAG 2.2 AA concepts across formats such as Word, Excel, PowerPoint, Markdown, PDF, EPUB, HTML, and CSS.

Current local inventory checked May 13, 2026:

Asset Type Count
Agent files (*.agent.md) 5
Prompt files (*.prompt.md) 5
Instruction files (*.instructions.md) 1
Skill files (SKILL.md) 1

What GLOW Does

  • Audits Word, Excel, PowerPoint, Markdown, PDF, EPUB, HTML, and CSS for accessibility issues.
  • Auto-fixes Word document issues where the change is deterministic, such as fonts, spacing, emphasis, headings, and margins.
  • Generates ACB-compliant Word templates.
  • Converts documents to Markdown, accessible HTML, Word, EPUB 3, PDF, and DAISY-oriented outputs through MarkItDown, Pandoc, LibreOffice, and related tooling.
  • Provides web, desktop, CLI, VS Code, and Word add-in surfaces.
  • Supports standards profiles such as ACB 2025 Baseline, APH Submission, and Combined Strict.

Why Choose GLOW

  • You care about documents, large print, Office files, or accessible publishing.
  • You want a smaller agent surface where one contribution can make a visible difference.
  • You want to connect agents to a real product workflow: upload, audit, fix, convert, template, export, review.
  • You want to help users who may not think of themselves as developers.

Good GLOW Contributions

  • Add a GLOW agent that helps users choose between Audit, Fix, Template, Export, and Convert workflows.
  • Improve the existing large-print agent instructions with clearer responsibilities and guardrails.
  • Add a prompt for reviewing release notes against current GLOW features.
  • Add custom instructions for web UI accessibility, plain-language findings, or large-print documentation consistency.
  • Write documentation that explains how contributors should test document accessibility changes.
  • Draft an issue for a future agent, such as a plain-language findings reviewer, batch-audit triage assistant, or Word add-in accessibility reviewer.

GLOW Safety Notes

  • GLOW handles documents that may contain personal, educational, medical, or organizational information. Do not put private user documents into public prompts or issues.
  • Auto-fix workflows must be conservative. An agent should explain proposed fixes and preserve author intent.
  • Large-print rules can affect pagination and layout. Document tradeoffs instead of pretending every fix is neutral.
  • When a rule comes from ACB, APH, Microsoft Accessibility Checker, or WCAG, cite the source or name the profile.

5. Project Option: Another Repository

You may choose another repository if the contribution is meaningful and reviewable. This can be your own project, a classmate's project, a community repository, or another open source project you care about.

Requirements for Another Repository

  • The work must help the repository, not just satisfy the workshop.
  • The contribution must have a clear audience.
  • The contribution must be small enough to review.
  • The contribution must include responsibilities and guardrails when it involves an agent or automated workflow.
  • If you cannot open a pull request, write a review-ready issue or contribution plan instead.

Good Contributions in Any Repository

  • Add .github/copilot-instructions.md that teaches Copilot the project's accessibility and contribution standards.
  • Add a custom agent for triaging issues, reviewing docs, checking release notes, or auditing accessibility.
  • Add a prompt file for a repeated maintainer task.
  • Improve issue templates or PR templates so contributors provide better accessibility context.
  • Write contributor documentation that explains how to test with keyboard, screen reader, and high contrast workflows.

6. Define Your Mission

A good capstone mission solves a specific, recurring problem. It does not try to do everything.

Write a one-sentence mission statement before editing files:

"My contribution helps [who] by [doing what] when [in what situation]."

Examples:

  • "My agent helps GLOW contributors by checking whether release notes describe user-facing document accessibility changes clearly."
  • "My prompt helps Accessibility Agents maintainers by turning a release note into repo documentation updates with screen reader, low vision, and sighted guidance."
  • "My custom instructions help my project avoid inaccessible React patterns when Copilot generates forms and dialogs."

Post this mission statement in your Challenge 16 issue comment so a buddy or facilitator can give early feedback.


7. Write or Improve the Agentic Asset

Your asset may be an agent file, prompt file, instruction file, skill, or documentation update. If you are writing an agent, use the structure below.

Agent File Location and Naming

Follow the target repository's conventions. Common locations include:

.github/agents/your-agent-name.agent.md
agents/your-agent-name.agent.md
community-agents/your-agent-name.agent.md

Use lowercase with hyphens. Example: .github/agents/plain-language-findings.agent.md.

Minimal Agent File Template

---
name: "Plain Language Findings Reviewer"
description: "Reviews accessibility audit findings for plain language, actionable remediation, and user impact."
---

# Plain Language Findings Reviewer

You are an accessibility documentation specialist focused on making audit findings clear, actionable, and respectful.

## Responsibilities

- Review finding text for plain language and specific remediation steps
- Identify vague phrases that do not explain user impact
- Check that findings name the affected workflow or assistive technology when known
- Suggest revised wording without changing the technical meaning

## Guardrails

- Never claim a finding is fixed unless the user provides verification evidence
- Do not remove severity or WCAG references
- If the technical meaning is unclear, ask for clarification instead of guessing
- Preserve project terminology unless it is inaccurate or inaccessible

YAML Frontmatter Fields

The following table describes the common agent frontmatter fields.

Field Required Description
name Yes Display name for the agent
description Yes One-sentence description of what the agent does and when it should be used
tools Project-specific Tool list when the target platform requires explicit tools

Learning Cards: Writing the Asset

Screen reader users
  • Use the Command Palette to create or open files, then save the asset in the target repository's expected folder.
  • Use Ctrl+Shift+O to move by heading and confirm that Responsibilities and Guardrails are easy to find.
  • Use Alt+F2 for long Copilot responses while testing the agent.
Low vision users
  • Keep frontmatter fields on separate lines and use a consistent heading hierarchy.
  • Use Markdown Preview to verify that headings, lists, and examples are visually clear.
  • Avoid long single-line bullets that require horizontal scrolling at high zoom.
Sighted users
  • Use the Outline view to scan the structure before testing.
  • Compare your file with two existing examples in the target repository.
  • Check that the file name, name, and description all point to the same focused mission.

8. Test Locally

Before opening a pull request, test or review your work.

Testing With GitHub Copilot Chat

  1. Open VS Code with the target repository.
  2. Save your agent, prompt, instruction, or documentation file.
  3. Open GitHub Copilot Chat (Ctrl+Alt+I) or run Chat: Open Chat from the Command Palette.
  4. Invoke the agent or prompt if supported. Example: @plain-language-findings review this audit finding for clarity.
  5. Observe whether the output follows the responsibilities and guardrails.
  6. Revise the asset and test again.

Testing Checklist

  • The contribution has a clear mission.
  • Responsibilities are specific and action-oriented.
  • Guardrails prevent overreach.
  • Output is useful, specific, and accessible.
  • The contribution follows the target repository's naming and folder conventions.
  • You documented any limitations or future work.

9. Open or Prepare Your Pull Request

Tool Cards: Open Your Capstone PR

VS Code Desktop:

  1. Push your branch: Ctrl+Shift+P then Git: Push.
  2. Run GitHub Pull Requests: Create Pull Request from the Command Palette.
  3. Set the base repository to the project you chose.
  4. Fill in the title and description.

GitHub.com:

  1. Navigate to your fork on GitHub.
  2. Activate Contribute then Open pull request.
  3. Verify the base repository and compare branch.
  4. Create the pull request.

GitHub CLI:

git push -u origin your-branch
gh pr create --repo OWNER/REPOSITORY

PR Description Checklist

  • Mission statement
  • Repository path chosen: Accessibility Agents, GLOW, or another project
  • What changed
  • Why it matters
  • How you tested it
  • Known limitations or follow-up ideas
  • Accessibility impact

Challenge 16 Evidence

Post one of these in your Challenge 16 issue:

  • A pull request link
  • A branch link with the changed file
  • A draft agent file pasted or linked
  • A contribution plan with mission, responsibilities, guardrails, and target repository
  • A review of a peer's capstone PR or a peer-simulation PR

If you use the Accessibility Agents autograder path, it checks agent file structure in agents/ or community-agents/: frontmatter, responsibilities, and guardrails. If you choose GLOW or another project, your facilitator reviews the evidence against the same principles.


10. Respond to Review

After you submit or share your capstone, a buddy, facilitator, or maintainer may review it.

Reviewers look for:

  • Clarity: Can someone understand the contribution in 10 seconds?
  • Specificity: Are responsibilities concrete and actionable?
  • Safety: Do guardrails prevent harmful or overconfident behavior?
  • Usefulness: Would this help a real user or maintainer?
  • Fit: Does it follow the target repository's conventions?

Respond to review one comment at a time. If a reviewer asks for a change, make the edit, commit, push, and reply with what changed.


11. Capstone Rubric

The capstone is assessed as a real contribution, not just as a file format exercise.

Core Criteria

The following table lists the capstone evaluation criteria.

Criterion Meets Expectations
Repository choice The learner can explain why the chosen repository benefits from the contribution
Mission clarity The contribution has a focused mission statement
Responsibilities The agentic asset names concrete actions it should perform
Guardrails The contribution includes boundaries, limitations, or safety notes
Accessibility impact The work accounts for screen reader, low vision, keyboard-only, cognitive, or document accessibility needs when relevant
Evidence The learner provides a PR, draft, branch, issue, or contribution plan
Review readiness The contribution is small enough for someone else to review

What Exceeds Expectations Looks Like

  • The contribution includes examples of expected input and output.
  • The PR description explains tradeoffs and limitations.
  • The learner tests with Copilot Chat or the VS Code Agents window and documents the result.
  • The learner responds thoughtfully to review feedback.
  • The contribution improves existing documentation, counts, or setup instructions alongside the agentic asset.

12. If You Get Stuck

The following table lists common capstone blockers and recovery steps.

Problem What To Do
I cannot choose a repository Choose Accessibility Agents if you want the clearest agent path, or GLOW if you want document accessibility and large-print impact
I cannot think of an idea Find one repeated maintainer task and write an agent or prompt for that task
I do not have permission to open a PR Create a draft in your fork or write a contribution issue with mission, responsibilities, and guardrails
The repository has no agents yet Add repo-level custom instructions or propose the first agent in a draft issue
My agent does too much Split the mission until it fits one sentence
Copilot ignores the guardrails Make the guardrails more explicit and test with the same prompt again
The external project has different conventions Follow that project's README and CONTRIBUTING file first, then explain any uncertainty in your PR
I finished but I am not sure I did it right Compare your work against the Challenge 16 reference solution, then ask for review

The Universal Safety Net

If everything else fails, post this on your Challenge 16 issue:

I attempted the capstone project and here is what happened:

Repository I chose: [repository] What I tried: [specific actions] What I expected: [what should have happened] What actually happened: [error or unexpected result] What I learned: [even from failure, what do I understand now?]

This is always useful evidence. A learner who explains a failure thoughtfully has learned more than one who followed the happy path without thinking.


Next: Chapter 22: What Comes Next
Back: Chapter 19: Accessibility Agents
Related appendices: Appendix L: Agents Reference | Appendix K: Copilot Reference

Authoritative Sources

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