mthines
UserA personal collection of skills for AI coding assistants — covering code review, DX/UX analysis, TDD, holistic debugging, and developer productivity.
Categories
Indexed Skills (47)
github-actions-author
Authors fast, cheap, maintainable GitHub Actions workflows applying 2026 best practices: caching with `hashFiles` + `restore-keys`, parallelization via matrix + artifacts, reusability (composite actions for steps, reusable workflows for jobs), security (SHA-pinned actions, least-privilege `GITHUB_TOKEN`, concurrency), trackable errors (named steps, step summaries, annotations, and stdout/stderr that always reaches the run log so agents can act on failures), and feedback for comment-triggered runs (👀 acknowledgement reaction on start, 🚀/👎 outcome reaction plus a run-linked comment at the end). Two modes: `scaffold` (default) generates workflow YAML; `review` audits an existing workflow against the same rules. Use when creating CI/CD pipelines, optimizing slow workflows, deduping copy-pasted YAML across repos, or auditing workflow security. Triggers on "github action", "github workflow", "ci pipeline", "create workflow", "speed up ci", "review my workflow", "/github-actions-author".
ideate
Generates, stress-tests, and iteratively evolves ideas for a stated problem — product concepts, features, solution options, strategies — using research-grounded divergent/convergent agent loops: parallel persona generators (nominal-group simulation), independent judges scoring novelty, feasibility, impact, and fit on separate axes, and bounded recombination rounds gated by /confidence. Auto-triages run depth (quick in-context vs deep multi-agent; override with quick|deep). Use when brainstorming, exploring solution options, or pressure-testing a concept. Triggers on "brainstorm", "give me ideas", "help me come up with", "ideate on", "what could we build", "/ideate".
optimize-approach
Reviews whether a change takes the most optimal approach for its stated intent and, when it does not, researches the code, validates a concretely better approach via holistic analysis, and either proposes it (report mode) or applies it behind a confidence gate (apply mode). Judges four axes — codebase-fit, simplicity, performance, robustness — at the approach level, deferring line-level and failure-mode findings to code-quality, critical, and holistic-review. Stays silent when the approach is already optimal (quiet early-exit). A `plan` mode reviews a drafted plan's approach at plan time (aw-planner Phase 1) — the cheapest moment to switch. Called by the reviewer and pr-reviewer agents, the polish skill, and aw-planner as a default-on lens; also runnable standalone. Triggers on "is this the best approach", "better way to do this", "is this optimal", "optimize this approach", "rethink the approach", "/optimize-approach".
autonomous-workflow
Execute complete feature development cycles autonomously — from task intake through tested PR delivery — using isolated Git worktrees. Phase-based workflow (0–7) with optional companion skills for planning, quality gates, TDD, UX, code quality, docs, and CI verification. Companions skip silently if not installed. Triggers on "implement autonomously", "end-to-end", "in isolation", "in a worktree", or independent feature work. Invoke with /autonomous-workflow.
aw-create-plan
Create the plan artifact (plan.md + checks.yaml executable acceptance checks) in `.agent/{branch}/` from the current conversation context. Captures all Phase 0-1 discussion into a structured, self-contained document that enables context recovery and session handoff. On every invocation, writes plan.md and re-derives checks.yaml from the Acceptance Criteria; an immutable plan.vN.md snapshot is written only in opt-in snapshot mode (`Skill("aw-create-plan", "snapshot")`). Use after planning is complete and confidence gate passes — and again on every plan iteration (user-requested refinement or Phase 4 auto-replan). Triggers on create plan, generate plan, write plan artifact, regenerate plan, iterate on plan.
implement-suggestion
Implements review-comment suggestions across one or more PRs. Multi-PR mode (default when $ARGUMENTS contains PR URLs; empty $ARGUMENTS auto-detects the active PR) per PR: resolves a worktree, fetches every actionable comment from both human teammates AND AI code-review bots (claude[bot], coderabbitai[bot], …), validates each through /critical + /confidence, builds a structured suggestion-pack, and dispatches a worker subagent that applies each approved change as its own commit, pushes to the existing branch, and resolves the addressed review thread — so every handled comment ends up resolved and the PR is left clean. Fast-lane for mechanical edits, standard-lane via aw-planner for architectural changes. Free-text mode applies a single pasted suggestion in the current directory. Triggers on "implement suggestion", "apply review comments", "address PR feedback", "implement reviewer feedback", "fix PR comments", "/implement-suggestion". With --watch, loops the apply on a single PR — waiting for new review-bot c
holistic-analysis
Forces a full holistic re-analysis when a fix or refactor isn't working. Instead of continuing to patch in isolation, this skill triggers a structured step-back analysis that traces the entire execution path end-to-end — from entry point to exit — analyzing each block, every contract boundary, and the full data flow. Three modes: "fix" (default) for bugs and broken behavior, "refactor" for restructuring/improvement, and "review" for PR validation (returns structured intent-match + system-fit findings for the `pr-reviewer` agent to consume — never run on its own for routine review work). Trigger ONLY when at least one isolated fix attempt has already failed, or the user explicitly requests a full execution-path analysis — phrases like "step back", "think holistically", "analyze the whole thing", "zoom out", "look at the bigger picture", or "rethink this" qualify only in that context. Never trigger for trivial one-line fixes or first-attempt debugging. Also triggers on "/holistic", "/step-back", "/rethink", "/z
screen-recorder
Records short videos of specific page sections using Playwright's `recordVideo` API, plays scripted interactions (hover, click, focus, scroll, keypress), crops the output to a target element via `ffmpeg`, and saves a `.webm` (or `.mp4` / `.gif`) artifact to `.agent/recordings/`. Use when a still screenshot cannot prove the change — verifying a View Transition, a Motion `layout` morph, a hover stagger, a scroll-driven timeline, an `@starting-style` entry, or any multi-frame interaction. Called by the `animations` skill to validate a generated animation, by the `ux` skill to capture an interaction the `pr-reviewer` cannot read from code, and by the `pr-reviewer` agent to produce a local clip it can inspect on motion-heavy diffs. Triggers on "record this interaction", "capture this animation", "video of this section", "validate the transition visually", "screen recording", "/screen-recorder".
create-pr
Generate a short, narrative GitHub pull request description (≤ 25 lines, hard ceiling 40), push the branch, open the PR as a draft, then run the review-loop skill for a bounded review-apply-simplify convergence before finalizing. The review-loop (pr-reviewer → implement-suggestion → polish simplify, up to 5 iterations, converging until every review thread is resolved via fix or reply) runs AFTER the draft PR is open — the single reviewer now operates on PRs. Scale down with --no-review (skip the pr-reviewer pass), --no-simplify (skip simplify), --quick (light mechanical pass only), or --no-quality (skip the loop entirely). A post-push external-bot feedback loop also runs by default (--no-feedback to skip), scoped to external bots only so it does not re-apply the review-loop's own findings. With --split, analyses the branch diff and breaks it into 2–4 focused, dependency-ordered draft PRs after user approval. Escalates judgment-required CI failures via /confidence rather than guessing. Invoke with /create-pr,
storybook
Scaffolds, audits, and tests Storybook stories for React (web) and React Native / Expo (native) component libraries. Generates three artefacts in two files per invocation: a visual regression `*.stories.tsx` file containing a `Default` story (variants grouped into a single snapshot) and a `Playground` story (interactive `args` / `argTypes`), plus a sibling `*.test.stories.tsx` interaction test file under a `/Tests` namespace. Supports an opt-in, per-pathname auth flow whose credentials live in the OS keychain (not in the repo). Iteration loop uses the Playwright CLI against the running Storybook URL; visual evidence delegates to the `pr-reviewer` agent and the `screen-recorder` skill. Triggers on "scaffold stories", "add storybook", "story for this component", "interaction test for this story", "/storybook".
polish
Re-runnable pre-PR quality gate for the current branch. Composes two existing passes over the branch diff: a broad pr-reviewer pass (read-only review via the branch's open PR, which `pr-reviewer` requires) and a code-quality simplify pass (applies Class M mechanical refactors behind a confidence ≥ 90 % gate, reverting on failure). Run bare for the full review + simplify works; scope it with `review`, `simplify`, or the light `quick` mechanical pass. Commits each pass separately for traceability (`--no-commit` to skip). Use standalone any time mid-development to clean a branch. Note that `/create-pr` delegates its quality step to `review-loop` (the bounded convergence loop) post-draft, and the `review-loop` skill calls only `polish simplify` — never full `polish`. Triggers on "polish my branch", "clean this up before the PR", "review and simplify", "tidy up", "prep my branch", "/polish".
review-changes
Review branch changes or a PR for code quality, tests, documentation, and commit hygiene. Routes to the `review-loop` skill for a bounded review-apply-simplify convergence loop, or to `pr-reviewer` directly for a one-shot read-only review. Invoke with /review-changes.
aw-review-quality-gate
Self-check quality gate for review findings. Validates that each finding is actionable, evidence-backed, correctly located, not duplicating linter output, and not a false positive. Use after generating findings but before delivering them. Triggers on: "quality gate findings", "validate findings", "gate my review", "/aw-review-quality-gate".
interview
Aligns on the scope of a request before any plan or implementation begins — the requirements-elicitation interview a senior engineer runs before touching code. Restates the request and diffs it against the user's words, researches the codebase so questions are specific, surfaces unknowns, non-goals, edge cases, and success criteria, then runs a batched clarifying-question interview only when research cannot resolve the ambiguity (adaptive — stays silent when the request is already crisp). Produces a confirmed brief.md artifact that downstream planning consumes, plus a readiness verdict (ready / ready-with-assumptions / blocked). Convergent and pre-plan: hands option-generation to /ideate, plan review to /critical, and scoring to /confidence. Use before autonomous work, before planning, or when a request feels underspecified. Triggers on "align on scope", "interview me", "clarify the request", "scope this", "scope alignment", "before we plan", "/interview".
review-loop
Bounded review-apply-resolve convergence loop for a GitHub PR (draft PRs are fine). Runs up to N=5 iterations of pr-reviewer → implement-suggestion (--resolve-all) → polish simplify, converging until every review thread is resolved — through a fix OR a reply (answered question, recorded rationale) — so the PR is left with zero open threads (only genuine human-judgment flags stay open). On convergence it also refreshes the PR description to match the shipped diff and, best-effort, notes the linked Linear ticket. Use after opening a draft PR to converge the branch to a clean, review-ready state before undrafting. Callers: autonomous-workflow Phase 6/7, create-pr (post-draft), and standalone via /review-changes. Invoke with /review-loop <PR-URL|#n> [--cap N] [--critical] [--no-feedback] [--no-refresh].
playwright-trace-analyzer
Analyzes Playwright E2E `trace.zip` archives (and bare trace JSONL when unpacked). Extracts the action timeline, network waterfall, console errors, and DOM-snapshot anchors, then identifies the highest-impact problems (flaky waits, slow selectors, network bottlenecks, hung actions, unhandled console errors, navigation churn) and proposes concrete test or app fixes ranked by measured impact. Auto-detects whether the input is a `trace.zip`, a directory of unpacked trace files, or a single `trace.trace` / `trace.network` JSONL stream. Iterates via the `/confidence` skill — if root-cause certainty is below 90%, it digs deeper before recommending a fix. Use when handed a Playwright trace, asked "why is this test flaky?", "why did the test time out?", or asked to optimise an E2E suite with evidence. Triggers on "analyze trace", "playwright trace", "e2e trace", "test flake", "why did playwright fail", "playwright timing", "/playwright-trace-analyzer".
profile-optimizer
Analyzes React DevTools Profiler exports, Chrome DevTools Performance traces, and Chrome heap snapshots / heap-timelines / heap-profiles. Identifies the highest-impact bottlenecks (long tasks, expensive renders, layout thrash, wasted memoisation, blocking scripts, retained memory, leaks) and proposes concrete code fixes ranked by measured impact. Auto-detects the input format (React `.json` profile, Chrome trace `.json` / `.cpuprofile`, or `.heapsnapshot` / `.heaptimeline` / `.heapprofile`). Iterates via the `/confidence` skill — if root-cause certainty is below 90%, it digs deeper before recommending a fix. Use when handed a profile file, asked "why is this slow?", "why is memory growing?", or asked to optimise a hot path with evidence. Triggers on "analyze profile", "react profiler", "chrome performance", "optimize from profile", "profile this", "why is this slow", "memory leak", "heap snapshot", "/profile-optimizer".
rum-tracking
Guides product analytics and RUM (Real User Monitoring) event tracking in web (React/Next.js) and mobile (React Native/Expo) apps. Decides what user interactions are valuable to capture, what's noise, what's PII to avoid, and how to implement, audit, update, and remove tracking code cleanly. Covers event naming, property schemas, tracking plans, GDPR/CCPA/DPDPA compliance, OpenTelemetry semantic conventions for browser and mobile RUM, and platforms (PostHog, Segment, Mixpanel, Amplitude, Datadog RUM, Sentry, OTel, Dash0). Modes: guide (default), implement, audit, remove, plan. Triggers on "track this event", "add analytics", "what should I track", "is this PII", "tracking plan", "remove tracking", "audit analytics", "/rum-tracking".
video-analyser
Analyse a video file — primarily a screen recording of a bug — to extract errors, UI state, and reproduction steps. Resolves input from a Linear ticket URL, a local file path, or a direct video URL. Extracts keyframes with ffmpeg, runs optional Tesseract OCR and Whisper audio transcription, then delivers structured findings. Trigger phrases: "analyse this video", "analyze this recording", "what does this video show", "extract bugs from this recording", "analyse this screen recording", "investigate this mp4", "investigate this mov", "analyse this clip", "look at this screen capture", "what is happening in this video", "analyse this screen capture", "video-analyser", "/video-analyser".
create-skill
Scaffold, review, upgrade, or diagnose agent skills against best-practice frontmatter, progressive disclosure, token-aware structure, and the agent-skills.git symlink + inventory wiring. Modes: `scaffold` (default — new skill), `review` (audit existing skill), `upgrade` (split a single-file skill into multi-file), `diagnose` (retrospective failure analysis that emits a confidence-gated unified diff against any skill declaring a diagnostic surface). Triggers on "create a skill", "scaffold a skill", "new SKILL.md", "review this skill", "audit my skill", "upgrade this skill", "split this skill", "diagnose this skill", "why did <skill> miss this", "/create-skill".
docs
Authors, audits, and maintains project documentation across CLAUDE.md / .claude/rules/, AGENTS.md, README.md, and Diátaxis docs/ trees (root + nested for monorepos). Four modes: init scaffolds a tiered docs setup from scratch; update detects drift (dead @imports, renamed commands, stale narrative) and incrementally refreshes via a Placement Resolver that pushes rules to the innermost-ancestor destination; readme writes or audits a README against the standard-readme spec; audit produces a documentation health report across every surface. Routes by kind: hard rules to CLAUDE.md, path-scoped patterns to .claude/rules/, narrative to docs/, marketing to README.md. Triggers on "init claude", "bootstrap docs", "scaffold CLAUDE.md", "update docs", "sync CLAUDE.md", "docs drift", "write a README", "audit our docs", "review the README", "Diátaxis", "/docs".
optimize-claude-md
Audits CLAUDE.md files (root, nested, `.claude/rules/*.md`) for context bloat and emits ranked suggestions across two levers — (1) shrink inventory entries, (2) flag rarely-used agent-invokable skills that should become slash-only to drop their description from the always-on available-skills list. Triggers on Claude Code's "Large CLAUDE.md will impact performance" warning (> 40k chars), inventory entries duplicating harness-loaded skill descriptions, "CLAUDE.md is too big", "shrink CLAUDE.md", "optimize CLAUDE.md", "/optimize-claude-md". Three modes — `audit` (read-only ranked report + slash-conversion candidates), `trim` (interactive one-line hook + diff approval), `extract` (moves sections to linked files preserving content). Composes with `docs` (Placement Resolver) and `create-skill` (invocation matrix). Hard rules: refuses files < 10k chars; never deletes silently; never edits any skill's canonical `SKILL.md` frontmatter — routes to `/create-skill`.
persistent-memory
Persists context across conversations as plain markdown so every future session can enrich a topic-scoped memory (e.g. `parenting`, `relationship-anna`, `work-history`, `project-acme`). Four operations: `write` (extract candidates, resolve as ADD / UPDATE / DELETE / NOOP per Mem0), `read` (load a ≤ 200-line INDEX; fetch detail entries on demand per Claude Code's MEMORY.md pattern), `consolidate` (sleep-style merge + prune), `forget` (delete or redact with audit). Three storage tiers: home (`~/.agent-memory/<scope>/`, default), project-local (gitignored), project-shared (committed). Strict never-store list (passwords, API keys, JWTs, credit cards, SSNs, private keys); mandatory consent preview before write. Documents scaling from markdown → SQLite FTS → vector DB → managed memory (LoreKit / Mem0 / Letta / Zep). Documents the LoreKit backend the self-improvement loops now run on (`autonomous-workflow`, `fix-bug`, `batch-linear-tickets`, `implement-suggestion`, `ci-auto-fix`, `e2e-pr-stabilizer`, `test-auto-fix`
changelog
Generates a personal markdown changelog of merged or closed pull requests authored by the current user and Linear tickets the user closed or worked on, over a configurable window (default 7 days), grouped by feature area (e.g. Dashboards, Agent0). Inputs sourced from `gh search prs --author=@me` and the Linear MCP. Use for weekly recaps, status updates, performance reviews, or end-of-sprint summaries. Triggers on "changelog", "what have I done", "weekly summary", "my recent work", "recap my week", "/changelog".
ci-auto-fix
Diagnoses a failed CI check, classifies it with an explicit verdict (code-bug | workflow-bug | dep-bug | env-bug | flaky | unsure), confidence-gates the fix (>=90 auto, 80-89 ask, <80 escalate), applies it, pushes, and iteratively verifies until CI passes — reverting the last commit if a brand-new failure appears. Provider-agnostic in scope; currently implements the GitHub Actions path via `gh`. Hard- refuses to disable, skip, or weaken checks. Triggers on "CI is failing", "fix the CI", "the build is red", "auto-fix this PR's checks", "GitHub Actions failed", "/ci-auto-fix".
resolve-conflicts
Analyze and resolve Git merge/rebase conflicts intelligently, showing diffs and asking clarifying questions when needed. Invoke with /resolve-conflicts.
animations-native
Authors performant React Native / Expo animations with Reanimated and gesture handling with react-native-gesture-handler, running motion on the UI thread so it stays at 60/120 fps. Covers worklets, shared values, useAnimatedStyle, withTiming/withSpring, layout animations, the Gesture API (pan/pinch/drag/swipe), Moti, Lottie, Rive, reduced motion, haptics, and UI-thread profiling. Use when building RN motion, wiring a gesture, or when an RN animation feels janky. For WEB animations (CSS, Motion, View Transitions) use the `animations` skill instead. Triggers on "reanimated", "gesture handler", "react native animation", "expo animation", "useSharedValue", "withSpring", "moti", "swipe gesture", "drag", "pinch to zoom", "/animations-native".
animations
Authors performant web animations CSS-first AND brainstorms the right feedback for an interaction via a verb-to-motion catalog. Covers GPU-safe properties, modern primitives (@starting-style, interpolate-size), View Transitions, scroll-driven timelines, state-choreography morphs, React state (Motion, AnimatePresence), advanced effects (Liquid Glass, glow, 3D tilt), external engines (Lottie, Rive), React Three Fiber, prefers-reduced-motion, AND perceived performance (skeleton loaders, optimistic UI, loader floor, predictive prefetch, stale-while-revalidate). Use when building transitions, hover effects, route changes, when an animation feels janky, when deciding what feedback an interaction should have, or when the app needs to feel snappier. Triggers on "animate this", "fade in", "hover effect", "liquid glass", "lottie", "rive", "ideal feedback", "how should X feel", "skeleton loader", "perceived performance", "feel faster", "optimistic UI", "/animations".
ux
Reviews UX, accessibility, and microcopy for web and React Native (Expo) applications. Analyzes UI code against established UX principles, WCAG 2.2 accessibility standards, platform guidelines (Apple HIG, Material Design 3), and UX writing best practices. Triggers on: "ux review", "review ux", "check accessibility", "improve the UI", "ux audit", "review this component", "is this accessible", "check usability", "ux feedback", "review the design", "improve usability", "check contrast", "review navigation", "ux writing", "improve copy", "review microcopy", "make this more intuitive", "ux best practices", "/ux".
visual-design
Guides and reviews the visual design and brand identity of UI components for web and React Native — color systems, typography pairing, visual hierarchy, signature details, and named style directions (minimal, swiss, editorial, brutalist, neo-brutalist, glass, soft-UI, terminal, playful, retro). Owns the generative, brand-aware side; defers WCAG contrast math, size minimums, and dark-mode mechanics back to /ux. Modes: `guide` (default — build a component from scratch), `review` (audit existing visuals against direction), `direction` (propose a style direction for a new product or feature). Triggers on "visual design", "make this look good", "brand identity", "style direction", "improve the visuals", "review the look", "does this look generic", "/visual-design".
ai-engineering
Reviews and guides LLM/AI application engineering: prompt design, prompt caching, multimodal inputs, RAG, agent loops and tool design, resilience (rate limits, retries, fallbacks), memory, model migration, evals, testing, prompt-injection defence, and observability. Synthesises practices from Anthropic, OpenAI, Google, OWASP LLM Top 10, and practitioners (Hamel Husain, Eugene Yan, Chip Huyen). Triggers on "review my prompt", "design a system prompt", "optimise tokens", "set up RAG", "build an agent", "handle rate limits", "migrate to a new model", "write evals", "test my prompt", "audit AI code", "/ai-engineering".
code-quality
Language-agnostic skill for authoring and reviewing code with low cognitive complexity, readability, and long-term maintainability. Covers guard clauses, single-responsibility functions, type-driven design (illegal states unrepresentable, branded primitives, discriminated unions), schema-first validation, single source of truth for union metadata, functional core + imperative shell, idempotency, and neighbour-pattern symmetry. Pairs with `tdd` for new code (rules apply in GREEN/REFACTOR). Stack-specific extensions live under `rules/stacks/<stack>/` (React, Next.js today; drop a subdirectory for any other language or framework). Use during PR review, after writing new code, in TDD GREEN/REFACTOR, or when asked to "improve quality", "make this readable", "reduce complexity", "deduplicate", "clean this up", or "/code-quality".
confidence
Rates confidence that the current work fully solves the stated requirement. Supports plan validation, code review, and analysis (root-cause, refactor, diagnose) modes. Plan mode combines LLM judgment with deterministic rule checks (multi-signal gate); a failed rule caps the gate at 89% regardless of LLM score. Use before committing to autonomous execution, after implementation, or during investigation. Triggers on "confidence check", "validate plan", "rate confidence", "quality gate", "/confidence".
critical
Adversarially challenges a proposed plan, code change, or bug diagnosis from a hostile pre-mortem perspective. Walks a fixed taxonomy of failure modes, blast radius, rollback, hidden coupling, and maintainability; every finding must cite a file, line, or named assumption; forces a steelman of at least one alternative. Surfaces concerns only — does not score (delegates to `/confidence`) and does not apply fixes. Use during planning before autonomous execution, before opening a high-stakes PR, or when a fix "feels off". One adversarial pass per run — naïve self-refine loops amplify bias. Modes: plan (default), code, analysis. Triggers on "critical", "challenge this", "pre-mortem", "red-team this", "/critical".
tdd
Enforces strict Test-Driven Development with RED-GREEN-REFACTOR cycles. Writes one failing test at a time, implements minimal code to pass, then refactors. Delegates to the `test-provenance-guard` skill during REFACTOR to detect tests-by-construction (static + mutation checks). Pairs with the `code-quality` skill: invokes `Skill('code-quality')` during the REFACTOR phase to apply the full code-quality rule set against the GREEN output, and cites refactor recipes (R1–R20) by ID when reporting changes. Triggers on: "tdd", "write tests", "test this", "add test coverage", "test driven", "red green refactor", "/tdd".
test-provenance-guard
Detects tests that pass by construction — tests that define a private copy of the function under test instead of importing the production module — and self-heals by extracting the inline logic to an exported function, updating production callers, and rewriting the test to import the export. Two checks: (1) static — the test file must import the SUT and must not shadow its exported names; (2) mutation — blanking the production function body re-runs the test and expects failure. Runs autonomously inside autonomous-workflow Phase 4 and as a slash command for human-driven PR review. Use when adding new tests for existing or refactored code, when CI is green but you are unsure whether the tests actually exercise production, or when reviewing a PR for tests-by-construction. Triggers on "test provenance", "tests by construction", "verify tests cover real code", "tests duplicate logic", "mutation sanity check", "are these tests fake", "/test-provenance-guard".
e2e-pr-stabilizer
Stabilizes or optimizes Playwright E2E tests on one PR via a local-first loop, then ratifies with a single CI run. Pulls Dash0 spans (`git.pull_request_link`) as the historical baseline, then captures every iteration's evidence locally with `--trace=on` (same OTel exporter, same trace schema). Validation is empirical, not predictive: before commit, every new locator must resolve against source (static grep) or the live app (`locator.count()`); after commit, the fixed test must pass three consecutive local runs before the single push. Modes: `stabilize` (default) heals flaky / failing tests; `optimize` is report-only and ranks slow-action wins by measured ms saved. Refuses `.skip`, `.fixme`, `waitForTimeout`, or any check-weakening edit. Use when a PR has flaky or failing E2E tests or when you want to find slow tests worth tightening. Triggers on "stabilize this PR", "fix flaky e2e", "heal playwright on PR", "ui-e2e is failing", "self-heal e2e", "optimize e2e", "/e2e-pr-stabilizer".
e2e-testing-mobile
Plans, generates, runs, and heals end-to-end tests for Expo and React Native mobile apps using Maestro (the 2026 standard for RN E2E, adopted by Meta, Microsoft, and DoorDash, and integrated with Expo via EAS Workflows). Drives a spec-first YAML-flow loop, proposes `testID` source diffs (never `accessibilityLabel` reuse), runs Maestro Cloud as an EAS job, and stays token-aware via `--shards`, `--retries`, and failure-only healing. Use for native flows in Expo / RN apps. Triggers on "test this RN flow", "add mobile e2e", "maestro flow", "expo e2e", "e2e for react native", "test the native app", "/e2e-testing-mobile". Defer to [`e2e-testing`](../e2e-testing/SKILL.md) for web flows and the WebView portion of hybrid apps.
e2e-testing
Plans, generates, runs, and heals end-to-end tests using Playwright Test Agents (Planner, Generator, Healer) and the official `@playwright/mcp` server. Drives a spec-first feature-flow loop, proposes `data-testid` source diffs only when accessibility-tree locators fail, and stays token-aware via snapshot mode and `--last-failed` reruns. Use when adding E2E coverage, verifying a user journey, hardening a flaky flow, or wiring Playwright MCP into a repo. Triggers on "test this flow", "add e2e", "verify the user journey", "write e2e test", "feature test", "playwright agents", "/e2e-testing".
optimize-mock-data
Optimizes a directory of structurally-related JSON / JSONL mock fixtures by inferring a shared schema, detecting structural drift between files, normalizing formatting and key order, and optionally shrinking verbose payloads while preserving shape. Use when fixture files have grown inconsistent (mixed tabs / 2-space indent, reordered keys, fields present in some files but missing from others, megabyte-sized payloads), when adding a new mock that must match an existing set, or when preparing fixtures for a storage-cost-sensitive context. Four modes — `analyze` (default, read-only), `normalize` (rewrites files in place), `shrink` (caps verbose string fields), `trim` (reduces array cardinality without touching strings). Triggers on "optimize mock data", "normalize fixtures", "check mock structure", "audit mocks", "shrink test fixtures", "are these mocks consistent", "/optimize-mock-data".
test-auto-fix
Diagnoses failing tests across any project, classifies each failure as a test-bug, prod-bug, or unsure, confidence-gates the fix (auto-apply at >=90%, 80-89 ask, <80 escalate), applies it, and re-runs until green. Surface-driven: reads per-project configuration from a surface file keyed by normalised git remote URL. Bootstrap auto-detects the stack on first run and proposes a surface diff for user approval. Hard-refuses to delete tests, add .skip/.only, or weaken assertions. Regression-detects after every fix: reverts on new failure instead of stacking. Triggers on "fix my failing tests", "tests are red", "auto-fix tests", "heal the tests", "/test-auto-fix".
aw-setup
One-time (but safely re-runnable) setup flow that scaffolds a project's aw-tester aw-target: detects auth strategy, captures storage state, writes .claude/aw-targets/local.yml, and validates with a smoke spec. Re-runs detect the existing aw-target and only re-prompt for what broke or changed. Triggers on "/aw-setup", "setup aw-tester", "scaffold aw-target".
aw-create-walkthrough
Generate a walkthrough artifact (walkthrough.md) in `.agent/{branch}/` summarizing completed work for PR delivery. Gathers information from plan.md, git history, and test results to produce a comprehensive summary. Use at Phase 6 before creating the draft PR. Triggers on create walkthrough, generate walkthrough, write walkthrough artifact.
batch-linear-tickets
Batch-analyze and resolve multiple Linear tickets — bug fixes and feature work. For each ticket: classifies as bug or feature (auto from Linear labels, or via the --type flag), dispatches the appropriate per-ticket analysis (linear-ticket-investigator + rca-investigator for bugs, just linear-ticket-investigator for features), gates on confidence, correlates findings across tickets, asks for user approval, then fans out aw-planner + aw-executor to ship PRs. Posts PR links back to each Linear ticket on completion. Triggers on "batch-linear-tickets", "batch analyze", "solve these tickets", "implement these tickets", "analyze tickets", "/batch-linear-tickets".
fix-bug
Resolves a single bug from any starting evidence — Dash0 telemetry (span / log / web event / RUM error link), raw stack trace, error message, code pointer (file:line), screen recording, Linear ticket URL, or free-text symptom. Classifies the input, **triages complexity** (Phase 0.5) to pick between a fast lane and a full holistic-analysis lane, runs a pre-flight sweep, locks a failing reproduction (delegating to /tdd, /e2e-testing, or /e2e-testing-mobile by layer), delegates root-cause analysis to the isolated rca-investigator agent (holistic-analysis + confidence) on complex bugs (or runs a lightweight in-skill analysis on simple ones), gates on confidence(analysis), and on >= 92 % hands off **without human confirmation**: simple bugs take the fast lane (/fix-bug → aw-create-plan → aw-executor, no aw-planner) and complex bugs take the standard lane (aw-planner → aw-executor), both with a CEGIS refinement contract. Fast-lane round-3 CEGIS failure falls back to standard-lane via aw-planner. An independent bug-
charting
Selects the right chart type and visualization library for React/Next.js (web) and Expo/React Native (mobile) data visualization tasks, then applies accessibility and anti-pattern guardrails. Maps data shape and intent (comparison, composition, distribution, relationship, evolution, flow, geographic, hierarchical) to a recommended chart, then to a recommended library based on platform, dataset size, and design system. Defers cross-cutting UI concerns (contrast, touch targets, typography, copy) to the `ux` skill rather than restating them. Triggers on: "what chart should I use", "visualize this data", "build a chart", "build a dashboard", "data visualization", "pick a chart library", "graph this", "/charting".
dx
Developer Experience (DX) review and advisory skill for CLI tools, shell scripts, developer tooling, and automation. Analyzes code against established CLI design guidelines (clig.dev, Heroku CLI Style Guide, 12 Factor CLI), composability principles, error handling best practices, and developer ergonomics. Triggers on: "dx review", "review dx", "check cli", "improve the cli", "dx audit", "review this tool", "is this usable", "check ergonomics", "dx feedback", "review the script", "improve usability", "check error handling", "review output", "dx writing", "improve help text", "review flags", "make this more intuitive", "dx best practices", "/dx".
Bio shown is the top-scored skill's repo description as a fallback — real GitHub bios land in a future update.