Sets up Prometheus scrape jobs targeting the Supabase metrics endpoint and configures log drain pipelines. Establishes monitoring dashboards and alerting baselines. Use when configuring Supabase monitoring, setting up Prometheus metrics, implementing log drains, or establishing observability for production Supabase deployments.

Creates Postgres triggers that fire database webhooks to Edge Functions or external endpoints on INSERT/UPDATE/DELETE events. Configures pg_net for HTTP callouts and payload serialization. Use when implementing event-driven workflows, database webhooks, trigger-based notifications, or automated pipelines on table changes.

Configures Edge Functions to use EdgeRuntime.waitUntil for background work while returning immediate 200 OK. Routes massive async workloads through pg_cron discovery and pgmq task queuing. Use when building background processing, async third-party calls, long-running edge function tasks, or webhook-driven pipelines.

Creates Postgres functions to validate storage path payloads and prevent directory traversal. Enforces tenant-safe file paths via storage RLS bucket policies. Use when configuring Supabase storage buckets, writing storage RLS policies, or implementing tenant-scoped file uploads.

Enforces that service_role key is never exposed to client-side code. Validates admin client isolation, privileged operations routing, and server-only key usage. Use when implementing admin operations, server-side Supabase clients, or auditing service_role key usage.

Generates Postgres Auth Hook that injects tenant_id and serialized permissions into JWT app_metadata using jsonb_set. Use when implementing RBAC, multi-tenant JWT claims, custom access token hooks, or permission injection into Supabase auth tokens.

Guided setup for TripIt→Reclaim travel timezone sync credentials. Validates environment variables and runs a dry-run to confirm everything works. Use when the user wants to set up, configure, or troubleshoot the TripIt to Reclaim calendar sync, API keys, or integration connection.

Run the TripIt→Reclaim travel timezone sync and interpret its JSON output. Handles no-change silence, change summaries, overlap warnings, and errors. Use when the user asks to sync time zones, update Reclaim from TripIt, check travel schedule sync, or run the calendar timezone update.

Generate, review, and curate eval scenarios for Tessl skills. Handles scenario generation, bleeding/leaking detection, criteria quality checks, coverage gap analysis, and score-driven iteration. Use when creating test cases or test scenarios for a skill, evaluating or assessing skill quality, running evals or evaluations, reviewing existing evals, expanding eval coverage, or skill testing.

Prune, trim, and shape an existing Tessl eval suite. Run the suite, compute per-scenario lift, apply the three-cause diagnosis to near-zero-lift scenarios, decide keep / fix / retire, and verify the curated suite still pulls weight. Use when an eval suite has grown bloated, scenarios are producing near-zero lift, reviewing an existing suite for trim opportunities, optimizing a suite for cost / signal ratio, many scenarios feel redundant or low-value, or the user says trim / prune / shape / curate / optimize the evals.

Scaffold the `jbaruch/coding-policy` gh-aw PR review workflows into a consumer repository: copies the packaged paired workflow templates (OpenAI + Anthropic reviewers), compiles them with `gh aw`, and opens a PR. After merge, every pull request in the repo is reviewed against the latest published `jbaruch/coding-policy` rules by the reviewer whose family differs from the PR's declared author model — avoiding self-review bias per `rules/author-model-declaration.md`. Use when the user wants to add, install, enable, scaffold, set up, or wire up an automated policy review / PR reviewer / coding-policy CI reviewer in a consumer repo. Also use to upgrade, update, refresh, or pull the latest reviewer templates into a consumer repo that already has the scaffold installed — the skill switches to override mode in that case.

Interview stakeholders to clarify ambiguous or underspecified requirements before writing code. Use when receiving a new task, feature request, or bug report that lacks clear acceptance criteria. Produces clarified requirements ready for spec authoring. Common triggers: "new feature", "build me", "implement", "add support for", or any task where requirements are vague or incomplete.

Verify that implementation and tests remain synchronized with specs after code changes. Use when code has been generated or modified from specs, after implementation is complete, or when reviewing a PR that touches spec-covered code. Reports mismatched targets, broken test links, and undocumented behavioral changes. Common triggers: "verify the spec", "check spec alignment", "are specs up to date", or after completing implementation work.

Create or update .spec.md files from clarified requirements. Use when requirements have been gathered and confirmed, and specs need to be written or updated before implementation begins. Produces well-structured spec files with frontmatter, requirements, and test links. Common triggers: "write the spec", "update the spec", "create a spec for", or after requirement-gathering completes.

Use when the user asks to run E2E tests, verify a web page, generate tests for an app, prove destructive actions are blocked, check if a UI element is visible, fill out a form, or drive a browser with natural language. Returns per-step results with safety classifications, policy decisions, DOM diffs, structured page context, and a signed audit trail.

Runs a structured 10-check pre-submission checklist against an open-source contribution before the contributor opens a pull request. Use when the user has written code for an open-source project and needs to prepare a PR, submit a contribution, or verify readiness. Triggers on "submit a PR", "open a pull request", "prepare the contribution", "ready to merge", "check my pull request". IMPORTANT — run this AFTER code is written but BEFORE submission. Checks: AI policy compliance and disclosure (including voluntary disclosure when no policy exists), diff size and focus, PR template, code style, commit conventions, tests, changelog and metadata, legal requirements (DCO/CLA), agent artifacts, slop detector patterns, and human ownership verification.

Analyzes project contribution guidelines, identifies the right venue (pull request, issue, discussion, RFC/KEP/DEP), checks issue metadata (claims, assignments, labels), searches for prior rejected attempts, and drafts proposals formatted to project templates. Use when the user wants to contribute to an open-source project, fix a bug, submit a PR, improve or refactor code, asks where to submit a change, or needs help choosing between PR/issue/discussion/RFC. Triggers on "fix this issue", "submit a PR", "refactor this", "improve this code", "open a pull request". IMPORTANT — run this AFTER recon and BEFORE writing code to verify the right venue and check for prior attempts.

Analyze an open source project's contribution norms, AI policy, conventions, and recent PR history before writing any code. Use when the user wants to contribute to an open source or GitHub project, fix a bug, submit a pull request, open a PR, make a contribution, or asks about contribution guidelines. Triggers on phrases like "fix this bug", "submit a PR", "contribute a fix", "open a pull request", "help me contribute", "how do I contribute", "what are the rules for this OSS project". IMPORTANT — run this BEFORE writing any code for an open source project.

Open and warm up a cv2.VideoCapture reliably, probe for real (non-black) frames before starting the main loop, and handle macOS index enumeration quirks. Use when a VideoCapture call succeeds but returns black/stale frames, when switching between built-in and USB webcams, or when the first ~5 seconds of a pipeline produce zero face detections.

Run expensive per-frame inference (face recognition, emotion classification, ViT embeddings) at a fraction of the capture rate so the camera loop stays responsive. Use when designing a vision pipeline that combines high-rate capture (30fps+) with heavy per-frame work (dlib, ViT, DeepFace) and you don't need every frame to be inferred.

Orchestrate sub-agents across Claude Code AND GitHub Copilot. Covers what inherits vs what doesn't on each platform, how to pass skills explicitly, and the echo-skills validation handshake. Use when spawning child agents, delegating tasks, building multi-agent pipelines, or troubleshooting why a sub-agent doesn't have access to expected skills or context.

Creates Postgres INSERT triggers that fire Edge Functions for document chunking and embedding generation. Configures the ingestion pipeline from raw document insert to vector storage. Use when building RAG ingestion, embed-on-insert pipelines, database-driven document ingestion, or automated embedding workflows.

Executes EXPLAIN ANALYZE via MCP to debug slow queries, identify missing indexes, detect sequential scans, and optimize query plans. Use when debugging slow SQL, analyzing query plans, finding unused indexes, optimizing Postgres queries, or investigating index-not-used issues.

Implements server-side auth session management with HTTP-only cookie synchronization for Next.js, SvelteKit, and other SSR frameworks. Depends on PKCE auth flow. Use when implementing SSR authentication, server-side session sync, HTTP-only auth cookies, Next.js Supabase auth, or SvelteKit Supabase auth.

Start a FastAPI dev server, verify docs and OpenAPI schema, test endpoints, and run pytest. Use when running, checking, or debugging a FastAPI application.

Scaffold a new FastAPI project with an opinionated directory layout, pydantic-settings config, and starter files. Use when creating a new FastAPI application from scratch.

Write professional, persuasive complaint letters to US airlines on behalf of passengers. Emphasizes loyalty status, DOT regulations, and the airline's own published commitments. Use when: user wants to complain to an airline, request compensation, write a complaint letter, dispute an airline's response, escalate an airline issue, file a DOT complaint, or mentions a bad flight experience they want to act on. Also trigger when user describes: flight delay, cancellation, lost baggage, damaged baggage, denied boarding, downgrade, poor service, broken amenities, tarmac delay, missed connection, or any airline service failure they want addressed.

Generates the visual layer of a talk: deck illustrations (FULL / IMG+TXT slides with a shared style anchor), progressive-reveal build chains, and YouTube thumbnails. Owns style-strategy collaboration (informed by the speaker's visual_style_history in the vault), prompt safety, edit-vs-regenerate asymmetry, build chaining, title-safe-zone composition, and thumbnail composition with a real speaker photo. Invoked by presentation-creator during illustration strategy (Phase 2), illustration generation and application to the deck (Phase 5), and the post-event YouTube thumbnail (Phase 7). Triggers: "illustrate the deck", "generate illustrations", "create slide visuals", "design the visual style", "make a thumbnail", "build a YouTube thumbnail", "add visuals to my talk", "regenerate slide image", "fix the thumbnail", "generate progressive reveals", "build sequence for a slide".

Creates new presentations grounded in the speaker's documented rhetoric patterns, using a personal rhetoric-knowledge-vault as a constitutional style guide. Follows an interactive, spec-driven process: distill intent from the user's prompt, jointly select rhetorical instruments from the vault catalog, architect the talk structure, develop content with speaker notes, run guardrail checks, generate a .pptx deck, and publish per the speaker's workflow. Use this skill whenever the user wants to create a new presentation, build a talk, write a conference submission, design a slide deck, prepare for a speaking engagement, or mentions "presentation" or "talk" in the context of content creation. Also trigger when the user describes a topic they want to present on, asks to adapt an existing talk for a new audience, or wants to develop a CFP abstract. Not a generic slide-deck tool — requires a populated rhetoric-knowledge-vault and follows the speaker's established style.

Runs interactive clarification sessions with the speaker after talk processing. Resolves ambiguities in rhetoric observations, validates findings, captures speaker intent, conducts humor post-mortems, and probes for blind-spot moments invisible to transcripts. Stores confirmed intents and infrastructure config in the tracking database. Triggers: "run clarification session", "humor post-mortem", "blind spot review", "capture speaker intent", "clarify rhetoric findings".