Project 18: High-Polish Property Inspector System

A dynamic Property Inspector that adapts by device type, validates in real time, supports dark/light theming, and includes contextual tooltips.

Quick Reference

Attribute Value
Difficulty Level 4
Time Estimate 14-22h
Main Programming Language TypeScript + HTML/CSS
Alternative Programming Languages JavaScript, Vue, Svelte
Coolness Level Level 4 (High UX craft)
Business Potential Level 4 (Conversion and retention driver)
Prerequisites Constraint-driven form design, Runtime schema revalidation, Accessible interaction patterns
Key Topics Configuration UX architecture

1. Learning Objectives

By completing this project, you will:

  1. Build a production-quality implementation of High-Polish Property Inspector System.
  2. Apply concept boundaries around Constraint-driven form design, Runtime schema revalidation, and Accessible interaction patterns.
  3. Validate behavior with explicit outcomes and failure-mode tests.
  4. Produce evidence artifacts suitable for review, support, and iteration.

2. All Theory Needed (Per-Concept Breakdown)

2.1 Constraint-driven form design

  • Fundamentals: This concept defines the first architectural boundary for this project. You should know the invariant conditions that must remain true during normal operation and failure operation. In Stream Deck plugin work, the most useful mindset is to treat interaction paths as explicit contracts, not ad-hoc callbacks, so behavior remains deterministic under context churn and profile switching.
  • Deep Dive into the concept: For this project, Constraint-driven form design is where correctness begins. Model state transitions explicitly, define allowed events, and reject illegal transitions early. Tie every side effect to context identity and traceability fields so debugging can reconstruct the full sequence. Design your test plan around race-prone paths first. Add failure classes and recovery transitions before polishing UX. This creates robust behavior under load and avoids hidden coupling across action instances.
  • How this fit on projects: This concept is the primary driver of runtime correctness in this project.
  • Definitions & key terms: invariant, transition contract, failure class, recovery path.
  • Mental model diagram:
Intent -> Validate -> Reduce -> Persist -> Render
  ^                                       |
  +--------------- Recover/Retry <--------+
  • How it works: model inputs, validate boundaries, reduce deterministic state, emit minimal side effects, then observe and recover.
  • Minimal concrete example:
PSEUDOCODE
if !isValid(event, state):
  return rejectWithHint()
next = reduce(state, event)
apply(next)
  • Common misconceptions: fast prototypes do not remove the need for explicit invariants.
  • Check-your-understanding questions: Which invalid transition causes highest user impact? Why?
  • Check-your-understanding answers: Any transition that mutates irreversible state without confirmation.
  • Real-world applications: production plugins that must survive long sessions and rapid profile switches.
  • Where you will apply it: project runtime handlers and teardown logic.
  • References: Stream Deck SDK docs + main sprint Theory Primer concepts 1/2/6.
  • Key insights: deterministic state design scales better than callback patching.
  • Summary: make invalid states unrepresentable and observable.
  • Homework/Exercises to practice the concept: draw one transition table and one failure table.
  • Solutions to the homework/exercises: each transition/failure should map to explicit UI feedback and test case.

2.2 Runtime schema revalidation

  • Fundamentals: Runtime schema revalidation handles data integrity and long-lived behavior. Treat user configuration, entitlement, and environment state as a schema-governed domain.
  • Deep Dive into the concept: Build validation at every boundary: PI input, backend receive, persistence write, and migration load. Use explicit versioning and conflict policy so stale updates cannot silently win. If sensitive fields exist, isolate them through secret-safe adapters and redact all diagnostics. This prevents corruption, race bugs, and support incidents that usually appear only after release.
  • How this fit on projects: ensures reliable persistence and predictable restart/recovery behavior.
  • Definitions & key terms: schema, migration, revision, redaction.
  • Mental model diagram:
Input Delta -> Merge -> Validate -> Version -> Commit -> Observe
  • How it works: merge safely, validate strictly, commit atomically, expose clear error feedback.
  • Minimal concrete example:
PSEUDOCODE
merged = merge(prev, delta)
assert schemaValid(merged)
save(merged, revision+1)
  • Common misconceptions: compile-time types are not runtime safety.
  • Check-your-understanding questions: Why must backend revalidate PI values?
  • Check-your-understanding answers: PI can be stale/malformed; backend is source of truth.
  • Real-world applications: paid plugins, sync features, and multi-account integrations.
  • Where you will apply it: persistence, entitlement checks, and API credential handling.
  • References: Stream Deck settings/secrets docs + RFC security guidance where applicable.
  • Key insights: data integrity is a user-visible feature.
  • Summary: strict boundaries prevent expensive post-release bugs.
  • Homework/Exercises to practice the concept: define v1/v2 schema and migration tests.
  • Solutions to the homework/exercises: include defaults, backward compatibility, and rollback path.

2.3 Accessible interaction patterns

  • Fundamentals: Accessible interaction patterns translates implementation quality into user trust, adoption, and maintainability.
  • Deep Dive into the concept: Build release and support workflows in parallel with features. Define observability schema, packaging checks, and non-functional budgets (latency, memory, retry behavior). Add diagnostics UX so users can self-report actionable data. If this project targets commercial outcomes, connect operational quality to listing confidence and retention. For hardware-diverse use cases, ensure adaptive behavior is explicitly tested across capability subsets.
  • How this fit on projects: provides the delivery and sustainment layer beyond core functionality.
  • Definitions & key terms: SLA mindset, supportability, release gate, degraded mode.
  • Mental model diagram:
Feature Build -> Validation Gate -> Pack/Release -> Observe -> Support -> Improve
  • How it works: define quality gates, ship artifacts, monitor signals, feed incidents back into design.
  • Minimal concrete example:
PSEUDOCHECKLIST
validate pass
smoke install pass
diagnostics export pass
rollback artifact present
  • Common misconceptions: once it works locally, release risk is low.
  • Check-your-understanding questions: Which quality gate catches packaging regressions earliest?
  • Check-your-understanding answers: deterministic CLI validate/pack + smoke install checks.
  • Real-world applications: marketplace submission, enterprise team deployment, paid support.
  • Where you will apply it: release checklist, diagnostics, and post-launch iteration.
  • References: Stream Deck CLI docs, marketplace docs, and reliability references.
  • Key insights: sustainable plugins are operated products, not one-off scripts.
  • Summary: build supportability and release discipline into the first milestone.
  • Homework/Exercises to practice the concept: create one pre-release gate matrix and one incident response runbook.
  • Solutions to the homework/exercises: each gate/runbook step must include pass/fail evidence.

3. Project Specification

3.1 What You Will Build

A dynamic Property Inspector that adapts by device type, validates in real time, supports dark/light theming, and includes contextual tooltips.

3.2 Functional Requirements

  1. Implement all user-facing behaviors listed in the source sprint project.
  2. Preserve deterministic state behavior under context churn and restart.
  3. Enforce boundary validation for configuration and external events.
  4. Expose clear feedback for success, pending, and failure modes.
  5. Provide release/support artifacts aligned with project scope.

3.3 Non-Functional Requirements

  • Performance: Remain responsive under expected event rates for this project.
  • Reliability: No orphaned timers/subscriptions after teardown paths.
  • Usability: Users can understand current state from key/PI feedback quickly.
  • Supportability: Logs and diagnostics must be actionable and redacted.

3.4 Example Usage / Output

“How do I make configuration feel fast and premium while still preventing invalid runtime state?”

3.5 Real World Outcome

When you select the action on different devices, the Property Inspector layout changes instantly:

  • key-only devices show compact controls,
  • dial-capable devices show additional encoder behavior panels,
  • invalid inputs show inline errors with guidance,
  • theme changes auto-switch color tokens,
  • tooltips explain risky options before save.

Users can close and reopen Stream Deck and all validated settings persist without reverting or corruption.

4. Solution Architecture

4.1 High-Level Design

Stream Deck Events -> Runtime Reducer -> Capability/Policy Layer -> Side Effects
        ^                                                          |
        +---------------------- Diagnostics/Observability <--------+

4.2 Key Components

  • Action Runtime Layer: Handles event routing, context scoping, and state reduction.
  • Policy Layer: Applies validation, feature gates, retries, throttles, and safety rules.
  • Feedback Layer: Produces deterministic key/dial/PI feedback from canonical state.
  • Persistence/Integration Layer: Manages settings, secrets, sync, and external API boundaries.

4.3 Design Questions (From Sprint)

  1. Dynamic layout logic
    • Which fields are always visible vs capability-gated?
    • How will you avoid layout shifts that confuse users?
  2. Feedback model
    • Which errors appear inline vs summary?
    • Which hints should be proactive tooltips?

5. Thinking Exercise (Before Building)

Design the Error Taxonomy

List every invalid setting state and define one user-facing correction message per state. Remove any message that blames the user.

6. Implementation Hints in Layers

Hint 1: Starting Point

  • Build field schemas first, then render controls from schema metadata.

Hint 2: Next Level

  • Add a stable messageId in PI->backend messages for response correlation.

Hint 3: Technical Details

PSEUDOFLOW
input change -> local validate -> send delta + messageId -> backend validate -> ack/error -> UI reconcile

Hint 4: Tools/Debugging

  • Log validation failures with field name, rejected value class, and context.

7. Verification and Testing Plan

  1. Unit-level: transition validity, schema validation, and policy decisions.
  2. Integration-level: PI/backend flow, persistence/restart, and dependency adapters.
  3. Failure-level: network/auth/retry/teardown behavior under injected faults.
  4. Release-level: validate/pack/smoke workflow and artifact integrity checks.

8. Interview Questions

  1. “How did you handle validation without creating noisy UX?”
  2. “How does your PI adapt for dial-capable vs key-only devices?”
  3. “Which accessibility checks did you automate?”
  4. “How do you prevent stale PI data from overwriting backend state?”
  5. “Which micro-interactions improved user confidence the most?”

9. Common Pitfalls and Debugging

Problem 1: “Settings appear saved but revert later”

  • Why: UI accepts value, backend rejects silently, no reconciliation state.
  • Fix: Add explicit ack/error channel and visible save state indicator.
  • Quick test: Force invalid input and verify inline + backend error match exactly.

10. Definition of Done

  • PI layout adapts by device/controller capabilities.
  • Real-time validation feedback prevents invalid submissions.
  • Dark/light themes are fully supported with accessible contrast.
  • Inline tooltips explain advanced options contextually.
  • Persisted state reloads consistently after restart.

11. Additional Notes

  • Why this project matters: Property Inspector UX quality is usually the largest difference between hobby plugin and paid plugin.
  • Source sprint project file: P18-high-polish-property-inspector-system.md
  • Traceability: Generated from ### Project 18 in the sprint guide.