Audit and reduce AI agent token and inference spend through context discipline, prompt caching, model routing, batching, and workflow capture. Use when discussing AI coding bills, token waste, model selection, prompt caching, or agent cost optimization.
Design regression tests for AI-assisted development by targeting model blind spots such as sandbox versus production path drift, response-shape mismatches, untested bug fixes, and same-model review failures. Use after AI-generated code changes, bug fixes, API edits, or feature-flag/sandbox changes.
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation. Use when preparing release notes, summarizing…
Correctness, security, and spec-fidelity gate for incoming pull requests. Auto-invoked when reviewing a diff, evaluating a PR, running /code-review at any effort level, or asked "is this safe to merge?" Covers bugs, TypeScript hygiene, security, database safety, test existence, devex regressions, feature-flag leaks…
Survey any codebase as a senior advisor, then hand back either prioritized self-contained implementation plans for OTHER models/agents to execute, or a written architecture and health analysis for humans. Strictly read-only on source code — never implements, fixes, or refactors anything itself. Use when asked to audit…
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
Generate Conventional Commit messages from staged or unstaged git changes, split unrelated changes into logical commits, detect breaking changes, and optionally create commits after approval. Use when writing commit messages, preparing commits, or committing local work.
Front door for a freshly reported failure: build a deterministic feedback loop, reproduce the symptom, rank falsifiable hypotheses, and instrument the narrowest point that separates them. Carries the lookup library — 54 rules across 10 categories covering observation technique, common bug patterns, and triage…
Single front door for deployment and infra provisioning. Parses a subcommand — app, compose, ec2, monitor, or devcontainer — and routes to the right engine: deploy (web app deployment to staging/production), deployment-composer (compose the smallest safe deployment workflow from repo signals), ec2-backend-deployer…
Run deployment workflows for web applications (staging, production). Use when user says 'deploy', 'push to staging', 'release', 'ship it', or 'go live'.
Compose deployment workflows from smaller skills and repo signals, including trunk-based releases, CI quality gates, provider deployment, post-deploy verification, rollback, and failed-check diagnosis. Use when the user asks for a deployment plan, release workflow, ship-to-staging/production environments, or a smart…