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Stephen Benjamin 4214189287 fix: repair broken skill references, fence nesting, and invisible unicode (#2568 )

While implementing the Agent Plugin v1 spec in https://github.com/stbenjam/skillsaw/pull/483, I used this repository as a canonical real-world source for tests. Along the way its checks surfaced genuine correctness issues worth fixing regardless of tooling:

- Internal links that do not resolve (22): wrong relative paths, links whose targets are runtime output paths rather than bundled files (now inline code), a schemeless external URL parsed as a relative path, and links to files that do not exist (removed).

- Bundled skill files never referenced from their SKILL.md (14): each is now cited from the section where it is used, so nothing ships unreachable from the skill's instructions.

- Unclosed or mis-nested code fences (11): markdown templates embedding code blocks now use four-backtick outer fences so inner fences nest instead of closing the template early and leaking example content as live markdown; also removed stray orphan fences and closed an unterminated block at end of file.

- Invisible unicode (1): removed a zero-width space from a code example, a copy-paste artifact invisible to reviewers.

2026-08-07 02:01:43 +00:00

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name, description

name	description
azure-smart-city-iot-solution-builder	Design and plan end-to-end Azure IoT and Smart City solutions: requirements, architecture, security, operations, cost, and a phased delivery plan with concrete implementation artifacts.

Azure Smart City IoT Solution Builder

Use this skill to rebuild and standardize a complete workflow for Azure IoT and Smart City solutions.

When to use it

Use this skill when the user asks for things like:

"I want to build an IoT solution on Azure"
"Smart City architecture for traffic, lighting, or waste"
"How do I connect devices, analytics, and alerts?"
"I need a roadmap and backlog for an urban platform"

Objectives

Convert a high-level idea into a deployable architecture.
Reuse existing Azure-focused skills whenever possible.
Produce concrete artifacts the team can implement.

Workflow

0) Mandatory documentation review (before any architecture)

Before proposing architecture or technology decisions that involve edge computing, review Azure IoT Edge documentation first:

https://learn.microsoft.com/azure/iot-edge/

Minimum pages to review:

What is Azure IoT Edge
Runtime architecture
Supported systems
Version history/release notes
Relevant Linux/Windows quickstarts for the scenario

If documentation cannot be consulted, state this explicitly and continue with clearly marked assumptions.

1) Scope and constraints

Collect and confirm:

City domain: mobility, parking, air quality, water, energy, public safety, waste, etc.
Scale: number of devices, telemetry frequency, retention, regions.
Latency and availability objectives.
Regulatory and privacy constraints.
Existing systems to integrate (SCADA, GIS, ERP, ticketing, APIs).

2) Capability map

Split the platform into layers:

Device and edge: onboarding, identity, firmware, OTA, edge processing.
Ingestion and messaging: command and control, event routing, buffering.
Data and analytics: hot path vs cold path, dashboards, historical analysis.
Operations: observability, incident flow, SLOs.
Governance: RBAC, secrets, policies, network isolation.

3) Azure service selection (reference)

Device connectivity: Azure IoT Hub, Azure IoT Operations, IoT Edge.
Event streaming: Event Hubs, Service Bus, Event Grid.
Storage: Blob Storage, Data Lake, Cosmos DB, SQL.
Analytics: Azure Data Explorer, Stream Analytics, Fabric/Synapse.
APIs and applications: API Management, App Service, Container Apps, Functions.
Monitoring: Azure Monitor, Application Insights, Log Analytics.
Security: Key Vault, Defender for IoT, Private Endpoints, Managed Identity.

4) Non-functional design

Define and document:

Reliability model (zones/regions, retries, dead-letter handling, replay).
Security controls (zero trust, encryption, secret rotation, least privilege).
Cost controls (retention tiers, rightsizing, autoscaling, workload scheduling).
Data lifecycle (raw, curated, aggregated, archived).

5) Delivery plan

Create a phased execution:

Phase 1: Pilot district or single use case.
Phase 2: Multi-domain integration.
Phase 3: City-scale rollout and optimization.

For each phase, include:

Exit criteria
Dependencies
Risks and mitigations
KPI set

Reuse other skills first

There are two sources of skills:

Runtime-provided skills (external to this repository): only available when the Copilot host environment exposes them.
Local repository skills (this repository): available as local files under skills/.

Runtime-provided Azure skills (optional)

If they are available in the execution environment, delegate to these specialized skills for deeper guidance:

azure-kubernetes
azure-messaging
azure-observability
azure-storage
azure-rbac
azure-cost
azure-validate
azure-deploy

Local repository alternatives (use in this repo)

When runtime skills are not available, prioritize existing local skills in this repository:

azure-architecture-autopilot for architecture generation and refinement.
azure-resource-visualizer for resource relationship diagrams.
azure-role-selector for role selection guidance.
az-cost-optimize and azure-pricing for cost and pricing analysis.
azure-deployment-preflight for pre-deployment checks.
appinsights-instrumentation for telemetry instrumentation patterns.

If no specialized skill is available, continue with this skill and keep assumptions explicit.

Required output artifacts

Always provide these outputs:

Smart City solution summary (scope, assumptions, constraints).
Reference architecture (components and data flow).
Security and governance checklist.
Cost and scaling strategy.
Phased implementation backlog (epics and milestones).

Output template

Use references/smart-city-solution-template.md to standardize outputs for each scenario, with this response structure:

Context and objectives
Proposed architecture
Technology decisions and trade-offs
Security, operations, and cost controls
Phased implementation plan
Risks and open questions

Guidelines

Do not jump to deployment before validating prerequisites.
Do not recommend single-region production for critical city workloads.
Do not omit operational ownership (who handles incidents, SLAs, change windows).
Clearly separate assumptions from confirmed facts.

5.3 KiB Raw Blame History