Architecture runtime topology

Skill Xopoko/plug-n-skills/plugins/architecture-intelligence/skills/architecture-runtime-topology

Ready-to-install skills and plugins for Codex, Claude Code, and AI coding agents: practical workflows for app delivery, architecture, research, design, and agent tooling.

Install

npx -y skills add Xopoko/plug-n-skills --skill architecture-runtime-topology

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

8 stars8 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Use when code work touches runtime shape: services, app/CLI/background flows, deployment/IaC, observability, resilience, external integrations, ownership, and runtime coupling.

SKILL.md

2.9 KB, as published. Nobody here has run it

Architecture Runtime Topology

Bundled commands use $PLUGIN_ROOT ($env:PLUGIN_ROOT in PowerShell; same path suffix) for the plugin root. Set it once: use the host's plugin-root variable when defined (Claude Code: PLUGIN_ROOT="$CLAUDE_PLUGIN_ROOT"), otherwise the absolute path of this plugin's root directory.

Use when the question is how the system runs, communicates, fails, scales, or is operated.

Inputs

Deployment: Docker, Compose, Kubernetes, Helm, Terraform, serverless, Procfile, platform manifests, CI/CD, release config.
Runtime config: env/config directories, service discovery, feature flags, schedulers/jobs.
Integrations: HTTP, gRPC, GraphQL, queues, topics, cache, database, external APIs, webhooks, batch.
Observability: logs, metrics, traces, dashboards, alerts, SLOs, health checks, incidents.
Resilience: timeout, retry, circuit breaker, fallback, bulkhead, rate limit, idempotency, backpressure, degradation.
Ownership: service owners, CODEOWNERS/OWNERS, runbooks, escalation paths, review gates.

Record paths and signal names only; never repeat secret values.

Probe

python3 "$PLUGIN_ROOT/scripts/architecture_probe.py" <repo-path> --json

Use runtime_topology as evidence inventory. It detects deployment artifacts and runtime signal names, not production truth.

Lenses

Topology: what deploys, what calls what, and which runtime edges matter.
Failure behavior: slow/down/partial/overloaded/inconsistent dependency response.
Observability: critical paths have actionable logs, metrics, traces, health checks, owners.
Deployment conformance: source boundaries and IaC/deployment boundaries agree or drift.
Operability: teams can diagnose, roll back, and safely change runtime dependencies.
Ownership: runtime-critical surfaces have source-backed owner or review path.
Time-driven state: identify where state lives and which timer, refresh, lifecycle, scheduler, or storage signal re-evaluates it. Elapsed time alone is not an emission trigger. Use async-state-consistency for lifecycle semantics, replay/publication authority, linearization, and controlled race proof.
Quality attributes: availability, reliability, latency, scalability, security, cost, operability.

Output

Compact: runtime summary, highest-impact coupling/resilience risks, evidence inspected, unknowns needing traces/config/owner input, next validation.

Durable: architecture_intelligence.runtime_topology.v1.

Do not infer production state from repo files alone. Do not treat an import as proof a tactic is correctly used. Recommend distributed-system patterns only when topology and quality-attribute scenarios justify them.