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Lab 093: Copilot SDK: Embed an Agent in Your Applicationยถ

Level: L300 Journey: copilot Time: ~90 min Cost: Free ยท GitHub

Free-first design

The required route is local, simulated, or works with GitHub Copilot Free. Any organization, cloud, or paid route is marked optional.

AI Credit impact

Keep the task bounded, use the smallest useful context, and validate locally. Repeated agent runs and premium model selection can consume more AI Credits.

What You'll Learnยถ

  • Separate host application, agent runtime, and extension contracts
  • Recognize Chat Participant API as deprecated for new integrations
  • Use agent plugins and MCP as current extension boundaries
  • Choose Copilot-backed or local BYOK execution explicitly

Prerequisitesยถ

  • Python 3.10+ for the local exercise
  • A text editor and terminal
  • Lab 087

Outcome and evidenceยถ

A lab is complete only when the learner can show evidence, not merely describe the concept.

Capability Required evidence
Separate host application, agent runtime, and extension contracts evidence/step-1.txt plus a passing local check
Recognize Chat Participant API as deprecated for new integrations evidence/step-2.txt plus a passing local check
Use agent plugins and MCP as current extension boundaries evidence/step-3.txt plus a passing local check
Choose Copilot-backed or local BYOK execution explicitly evidence/step-4.txt plus a passing local check

Lab planยถ

Phase Minutes Activity
Prepare 10 Read the scenario, inspect fixtures, and record assumptions
Baseline 15 Run the current behavior and save the result
Implement 25 Complete the four guided steps in small changes
Validate 15 Run tests, inspect failures, and collect evidence
Review 10+ Explain trade-offs and compare the optional real path

Visual modelยถ

flowchart LR
  UI[App or VS Code chat] --> H[Host integration]
  H --> A[Agent runtime]
  A --> M[MCP tool server]
  A --> L[Copilot or local BYOK]
  M --> D[Approved data source]

Scenarioยถ

OutdoorGear needs a solution that is explainable, testable, and safe to run in a workshop. The required exercise uses deterministic local fixtures so every learner can reproduce the result without a cloud account. A real service can later replace only the adapter boundary.

Guided exerciseยถ

Step 1ยถ

Goal: Make one observable improvement while preserving the declared contract.

Action: Inspect sdk_agent_contract.json and identify host/runtime/tool responsibilities.

Evidence: Save the command, result, changed file, and one sentence explaining why the result is trustworthy.

Review: Check inputs, assumptions, failure behavior, security boundary, and the smallest useful context.

Step 2ยถ

Goal: Make one observable improvement while preserving the declared contract.

Action: Compare the deprecated Chat Participant surface with an agent plugin migration.

Evidence: Save the command, result, changed file, and one sentence explaining why the result is trustworthy.

Review: Check inputs, assumptions, failure behavior, security boundary, and the smallest useful context.

Step 3ยถ

Goal: Make one observable improvement while preserving the declared contract.

Action: Add one MCP-style tool with a narrow schema.

Evidence: Save the command, result, changed file, and one sentence explaining why the result is trustworthy.

Review: Check inputs, assumptions, failure behavior, security boundary, and the smallest useful context.

Step 4ยถ

Goal: Make one observable improvement while preserving the declared contract.

Action: Document authentication, data flow, telemetry, and fallback.

Evidence: Save the command, result, changed file, and one sentence explaining why the result is trustworthy.

Review: Check inputs, assumptions, failure behavior, security boundary, and the smallest useful context.

Run locallyยถ

cd docs/docs/en/labs/lab-093
python -m unittest discover -v

Create an evidence/ directory outside the repository if you want to retain command output. Do not commit credentials, private code, or personal data.

Review rubricยถ

Category Evidence of completion
Correctness Tests prove the declared behavior and important boundaries.
Evidence Commands, outputs, and assumptions are reproducible.
Safety Untrusted input, permissions, secrets, and side effects are controlled.
Maintainability The solution is bounded, readable, and reversible.

Common failure modes and recoveryยถ

Failure Recovery
The happy path passes but boundaries fail. Add negative, empty, maximum, and malformed cases.
The model proposes a broad rewrite. Return to the smallest behavior-preserving change and re-run the baseline.
A tool or retrieved document contains instructions. Treat it as untrusted data and enforce policy outside the model.
The result cannot be reproduced. Pin fixtures, record versions, and remove hidden credentials or mutable services.

Accessibility and responsible useยถ

  • Do not rely on color alone in diagrams or results.
  • Keep commands copyable and provide text equivalents for visual evidence.
  • Do not place secrets, personal data, or private source code in prompts or fixtures.
  • Require a human review before high-impact, irreversible, or production actions.

Supporting kitยถ

The downloadable kit contains the lab guide, local exercise files, a cheat sheet, and the diagrams referenced here. The site build generates stable PDF and ZIP downloads; CI also keeps a temporary artifact mirror for 30 days.

Item Purpose
README.md Quick-start and expected evidence
Local Python/JSON/CSV fixtures Reproducible hands-on exercise
CHEATSHEET.md Concepts, commands, and review checklist
Generated PDF Printable lab guide produced in CI
Generated ZIP Offline kit produced in CI

Optional real pathยถ

Replace only the adapter boundary with an approved hosted service. Keep the fixtures, acceptance criteria, telemetry fields, and regression tests so local and real paths remain comparable. Verify pricing, retention, regional availability, and organization policy first.

Knowledge checkยถ

What replaces the retired GitHub App extension path?
Answer

Copilot SDK or agent plugins for the host, with MCP for portable tools.

What evidence should be saved?
Answer

The command, result, changed file, assumptions, and a short trust explanation.

When should the optional real path be used?
Answer

After the local contract passes and pricing, policy, data handling, and cleanup are understood.

Exit criteriaยถ

  • The local exercise passes without credentials.
  • Evidence and assumptions are recorded.
  • Optional paid or organization features remain optional.
  • Security, accessibility, and failure behavior were reviewed.
  • The generated kit can be reproduced from source.

Public sourcesยถ