uFawkesAI

Generate and maintain AI_STANCE.md for any uFawkes* repo. Use when onboarding a repo to the uFawkesAI suite, when reviewing AI policy currency, or when a new AI tool is being adopted. Implements DORA AI Capability 1.

Ensure graphify corpus is current and complete before each agent session. Define minimum AI-accessible documentation per repo. Use at session startup to verify internal context is available to AI tools. Implements DORA AI Capability 3.

15-minute JTBD + acceptance criterion exercise. Use before any spec session. Produces a discovery-brief.md that anchors the entire increment to a real user need and a measurable DORA outcome. Implements DORA AI Capability 6.

Enforce minimum documentation standard across uFawkes* repos. Use when auditing a repo before release, onboarding a new repo to the suite, or implementing roadmap item 0.6 (cross-repo README links). Directly supports DORA AI Capability 3 and the 2023 DORA finding that documentation quality amplifies all technical capabilities.

Create and manage DOJO content for platform engineering education and knowledge sharing.

Maintain AI_STANCE.md as a living document. Use quarterly or when a new AI tool is adopted. Handles review triggers, the three-bucket update process, socialization checklist, and cross-repo consistency. Companion to ai-stance skill.

Full user research methods for uFawkes product decisions. Use when the 15-minute discovery exercise is insufficient — when the riskiest assumption is untested, when user segments disagree, or when a major capability is being designed from scratch. Tier 3: Phase 2.

Compute the four DORA delivery metrics from uFawkesObs (Prometheus + Loki). Use when producing monthly DORA snapshots, validating post-release metric trends, or generating ROI evidence. Requires uFawkesObs running. Implements DORA AI Capabilities 2 and 7.

Quarterly developer feedback collection and analysis for the fawkes platform. Use to measure whether the IDP actually reduces cognitive load for the product teams using it. Implements DORA AI Capability 7 (Quality internal platforms) — the measurement half.

Execute the weekly release checklist for any uFawkes* repo. Use when an increment is ready to ship. Implements the write-once-ship-four-times pattern: README → CHANGELOG → GitHub Release → dev.to → LinkedIn → ufawkes.dev.

Monthly DORA ROI snapshot using the 2026 DORA ROI report five-dimension framework. Use when producing board-readable ROI evidence, quarterly LinkedIn posts, or Dojo 'proof it works' content. Requires dora-measurement snapshot. Tier 3: Phase 2.

Map the product value stream to identify bottlenecks consuming AI productivity gains. Use when DORA metrics plateau, when lead time is high despite fast coding, or when planning a major capability investment. Based on DORA AI Capabilities Model v2025.1 VSM chapter. Tier 3: Phase 2.

Record agent decisions for post-hoc analysis and audit. Use when reviewing agent behavior patterns or tracking decision trends over time.

Measure whether agent findings are actionable, accurate, and useful. Use when evaluating agent effectiveness or tuning agent prompts to reduce noise.

Emit OTEL spans when an agent starts and completes its task. Use when instrumenting an agent to measure duration, success rate, and invocation patterns.

Track which skills are loaded during agent invocations. Use when analyzing skill usage patterns, identifying dead skills, or optimizing context loading.

Emit and consume telemetry spans for agent invocations, skill loads, findings, and decisions. Use when instrumenting the agent system itself or when analyzing agent behavior patterns.

Generate GitOps overlays for each environment. Use when creating kustomize overlays with environment-specific configuration.

Turn plan into code, manifests, pipelines, and GitOps overlays. Use when implementing features, generating manifests, or creating pipeline configurations.

Break the specification into logical architectural components. Use when identifying system components, data flows, external dependencies, and boundaries.

Identify the components required to implement the design. Use when mapping architecture to concrete services, modules, pipelines, and GitOps components.

Define interfaces between components. Use when specifying API endpoints, data models, event schemas, and integration contracts.

Validate Kubernetes-related design decisions. Use when checking resource requirements, deployment patterns, network design, and secret usage in the design.

Convert specification into technical design. Use when creating architecture, defining components, interfaces, and data flows.

Ensure the Fawkes CLI provides a clean, intuitive developer experience. Use when validating command naming, help text, error messages, or interactive prompts.

Provide CLI commands that scaffold new components, pipelines, tests, and GitOps structures. Use when scaffolding new services, pipeline-spec.yaml, GitOps overlays, or test suites.

Generate new project components from templates. Use when scaffolding service boilerplate, tests, manifests, or workflows.

Ensure devcontainers run correctly inside Coder workspaces. Use when validating Coder template, workspace image, resource limits, or startup scripts.

Provide a reproducible, standardized development environment for all Fawkes projects using devcontainers. Use when validating devcontainer.json, Dockerfile.dev, required tools, or Coder compatibility.

Ensure all required tools for Fawkes development are installed and correct versions. Use when validating Node, Python, kubectl, kustomize, or Fawkes CLI versions.

Run a local Kubernetes cluster for development and testing. Use when starting kind/k3d, applying manifests, validating rollout, or checking logs.

Simulate GitOps updates locally without pushing to remote repos. Use when cloning GitOps repo locally, applying OBS updates, or validating manifest correctness.

Simulate PIPE, OBS, GitOps, and cluster behavior locally for fast feedback loops. Use when running local pipeline simulations, GitOps updates, or cluster deployments.

Set up local development environment. Use when configuring devcontainers, workspace bootstrap, or local simulation.

Install all project dependencies in a reproducible way. Use when installing Node/Python dependencies, validating lockfiles, or checking reproducibility.

Generate .env files for local development. Use when creating .env.local, populating required variables, or validating secrets are not committed.

Automate initial project setup for developers. Use when installing dependencies, generating environment files, configuring Git hooks, or bootstrapping local clusters.

Validate Kubernetes rollout behavior. Use when validating Deployment/StatefulSet rollout, readiness and liveness probes, or autoscaling behavior.

Validate that the deployed application behaves correctly after reconciliation. Use when validating rollout status, health checks, logs, metrics, or trace propagation.

Validate logs, metrics, and traces emitted by the deployed application. Use when validating log schema, Prometheus metrics, or OpenTelemetry traces.