Demo skill one used to verify global vs project install behavior across agents

Demo skill two used to verify global vs project install behavior across agents

Reference material for writing Rego/OPA policies in a specific domain — Kubernetes admission control, Terraform/CloudFormation infrastructure-as-code validation, HTTP API authorization (request body validation, rate limiting), RBAC/ABAC access control models, metadata annotations, or Regal linter compliance by rule category. Load this when rules.md's general Rego style rules aren't enough and you need worked examples or domain-specific patterns for one of these areas.

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.

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Summarize URLs or files with the summarize CLI (web, PDFs, images, audio, YouTube).

Gestisce il sistema di passaggio di consegne tra sessioni AI per qualsiasi progetto. Crea, aggiorna e legge file HANDOFF-N.md nella cartella .handoff/ del progetto, mantenendo una knowledge base persistente con documentazione (CLAUDE.md, PROMPTS.md, CLIENTS.md, WORKFLOW.md). Usa questa skill ogni volta che l'utente vuole: - Salvare lo stato ("crea handoff", "salva lo stato", "facciamo il punto", "chiudiamo la sessione", "riprendiamo domani", "passaggio di consegne", "freeze the context", "save state") - Riprendere da una sessione precedente ("riprendi da dove eravamo", "carica handoff", "resume", "continua da HANDOFF", "cosa avevamo fatto") - Inizializzare la knowledge base di un nuovo progetto ("/handoff init") - Aggiornare la documentazione persistente (CLAUDE.md, PROMPTS.md, CLIENTS.md, WORKFLOW.md) Suggerisci proattivamente la creazione di un handoff dopo sessioni lunghe con modifiche importanti, debugging complessi, o decisioni architetturali significative.

Traccia bug emersi testando una skill o un plugin, per guidarne l'upgrade. Controparte di handoff orientata al ciclo test → bug → fix di una skill specifica: crea/legge file BUG-N.md in `.handoffskill/<nome-skill>/` con uno STATUS.md aggregato. Usa quando l'utente segnala che una skill non funziona ("questo non funziona", "bug nella skill X"), vuole testarla sistematicamente ("testiamo la skill X"), o riprendere uno stato di test precedente ("riprendi i bug di X"). Invoca anche con "/handoff-skill".

Implement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks.

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 presentations grounded in the speaker's documented rhetoric patterns, using a personal rhetoric-knowledge-vault as a constitutional style guide. Interactive and spec-driven: distill intent, jointly select rhetorical instruments from the vault catalog, architect the talk, develop content with speaker notes, run guardrail checks, generate a .pptx deck, publish per the speaker's workflow. Use whenever the user wants to create a presentation, build a talk, write a conference submission, design a slide deck, prepare for a speaking engagement, describe a topic to present on, or adapt an existing talk for a new audience. Also handles CFP abstracts; the sessions catalog of submission-ready titles, abstracts, and outlines; and single post-authoring tasks on an existing talk — QR code, deck export, shownotes page, YouTube thumbnail, linking a recording. Not a generic slide-deck tool — requires a populated rhetoric-knowledge-vault and follows the speaker's established style.

Edit a talk-to-camera or demo screencast recorded in Camtasia for Mac (screen, camera and mic in one take) into a speaker-first video: plan cuts on sentence boundaries from Camtasia's own word timings, frame and zoom the screen evidence, audit the framing against the recorded pointer, generate the Camtasia project, correct the dynamic captions, time the YouTube chapters, and compose the thumbnail from frames of the take. Use when the user has a new Camtasia recording to edit, wants captions fixed, zooms adjusted, chapters or a description with time marks, or asks how to produce a screencast like a previous one.

Scaffold the good-oss-citizen contribution gate into a consumer repository: a `pull_request_target` GitHub Actions check that fails any pull request whose description lacks a contribution declaration — an "AI Disclosure" section or an explicit "no AI assistance" statement — plus the vendored detection script, a PR template, and the tessl.json dependency entry. The gate enforces an outcome (AI use is disclosed) on the PR side, where it cannot be bypassed; it does not, and cannot, prove a tool ran. Use when a maintainer wants to add, install, set up, scaffold, enable, or wire up a contribution gate / a PR check that requires good-oss-citizen or AI-use disclosure before contributing.

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.

Controls Govee H6056 Flow Plus light bars (smart LED lights) via cloud REST API with correct segment-to-bar mapping (Yankee=0-5, Golf=6-11), phantom-segment awareness (12-14 return 200 OK but do nothing), correct "off" semantics (rgb=(1,1,1), not (0,0,0)), and rate-limit guidance (~7 req/min sustained → pair with iot-actuator-patterns-kotlin debounce). Use when the user wants to control Govee H6056 light bars, change LED light colors or brightness, set bar segment colors, or automate Govee smart lighting scenes.

Use when the user proposes — or the agent detects — a deviation from constitutional defaults that requires an Architecture Decision Record. Triggered by proposals to extract microservices, drop foreign keys, denormalize without measured evidence, store transactional truth in Neo4j, skip Row Level Security, skip the transactional outbox, run destructive migrations, use database-per-service, or any explicit override of a constitutional principle. Drafts a structured ADR with context, decision, consequences, alternatives rejected, migration path, validation criteria, and constitutional sections affected — and refuses to proceed with the underlying work until the ADR is at least Proposed status.

Use when designing or reviewing database architecture for high-demand multi-tenant commerce platforms — including PostgreSQL schema design, foreign keys, indexes, JSONB usage, multi-tenant isolation with Row Level Security, transactional outbox, Neo4j GraphRAG projections, event sourcing decisions, audit logging, partitioning, expand/contract migrations, and product/inventory/order modeling for restaurants, boutiques, drugstores, retailers, distributors, grocery, hardware, or appliance businesses. Triggered by any request to design tables, design schemas, create migrations, model products/variants/inventory/orders/payments, choose between monolith and microservices, choose between PostgreSQL and Neo4j as source of truth, model multi-tenant data, design event flows, or review an ER diagram.

Use when reviewing or designing how Neo4j and GraphRAG interact with PostgreSQL transactional truth — including any feature involving recommendations, semantic product search, ingredient relationships, substitution suggestions, complementary products, AI-assisted discovery, vector search combined with graph traversal, or any proposal that puts orders, inventory, payments, prices, or tenant access rules into Neo4j. Evaluates architectural proposals for data boundary violations, identifies sync pattern errors between Neo4j and PostgreSQL, produces structured design review feedback with severity-ranked findings, counter-proposals with Mermaid diagrams, eventing changes, and re-projection plans. Triggered by mentions of GraphRAG, Neo4j, knowledge graph, recommendations engine, semantic search, vector + graph hybrid search, AI product discovery, or any design that crosses the PostgreSQL ↔ Neo4j boundary.

Register a new Docker Compose project on UGOS Pro (NASync) when the compose file lives in the nanoclaw repo. Plumbs the `/volume1/docker/PROJECT_NAME` directory symlink, the in-repo `.env` symlink, and the UGOS Pro SQLite registration row so the project appears in the Projects UI without UGOS rewriting the tracked compose file. Use when adding a new sidecar that needs UGOS Pro UI Start/Stop visibility, when wiring a repo-tracked compose project onto the NASync for the first time, when migrating an existing service to the symlinked-compose topology, or when asked to "register a UGOS project" / "add a sidecar to UGOS Pro".

List pending skills and rules on the NAS staging area. Shows what the agent has created or updated that hasn't been promoted to plugins yet. Use before running promote, or when the user asks what's on staging.

Sequential workflow for migrating an admin-plugin skill, rule, or script set into a per-chat overlay plugin. Audits cadence frontmatter, state-plane couplings, and cross-skill imports; moves files across two plugin repos; updates per-group additionalTiles config; ships each side through the publish pipeline; verifies live materialisation. Use when extracting an admin skill to an overlay, refactoring admin content into per-chat plugins, splitting capabilities out of nanoclaw-admin, or wiring additionalTiles for a freshly extracted overlay.

Generates code verifier/challenge pairs, exchanges authorization codes for sessions, sets secure HTTP-only session cookies, and configures server-side callback handling to implement the Proof Key for Code Exchange auth flow. Replaces implicit token-in-fragment flows by removing hash-based token extraction and localStorage usage. Use when implementing Supabase authentication, OAuth login, secure browser auth, SSR auth setup, or modern auth flow migration.

Checks upcoming trips for missing bookings (flights, hotels, accommodation) by reading the nightly-built `travel-db.json`, and warns when a hotel stay's TripIt location is a garbage value (a fee/rate note or blank) that needs a manual TripIt edit. Reports gaps for all upcoming trips — no date limit. Supports snooze state. Silent when all bookings are complete and every hotel location is a plausible address (or snoozed). Use when the user asks about upcoming travel plans, itinerary completeness, missing reservations, hotel address problems, or TripIt trip status.

The unified drive-block engine. Manages the travel-time / driving blocks on your primary calendar — drives to your flights, to your in-person meetings, and to a trip you drive to rather than fly. Use when the user asks about drive blocks, driving time, commute or travel-time blocks on their calendar, or drives to the airport, to a meeting, or to a hotel; when the operator replies to a drive notification to skip a meeting drive ('skip', 'skip 2 and 3'); when the operator says whether a trip is a drive or a flight ('drive', 'fly'); or when the operator reports a drive block that looks wrong or missing. Also runs on its own schedule.

Check seat availability or fare-class (upgrade) inventory on a flight, judge whether the seat already assigned is beaten by anything open, review seats across every upcoming flight at once, or create an ExpertFlyer alert. Actions - check fare-class/upgrade inventory (Z class, upgrade certificate, SkyTeam partner); check seats on one flight; judge a held seat against open inventory in its cabin and above; review upcoming flights for better seats; create a seat or fare-class alert; diagnose access. Use when the operator asks whether a seat is open, asks about Comfort+ / premium economy / business availability, asks whether their seat is the best available or worth changing, says check my upcoming flights for better seats, asks to be alerted when a seat or fare class opens up, or a new booking has just appeared.

Open and warm up a JavaCV OpenCVFrameGrabber reliably on macOS, probe for real (non-black) frames before starting the main loop, and skip virtual cameras (Insta360 Link, Snap, OBS, Continuity Camera) that hijack low indices. Use when an OpenCVFrameGrabber 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) at a fraction of the capture rate so the producer loop stays at 30 fps. Includes the 4× downscale pattern for Haar face detection, persisted-overlay technique for skipped frames, and Flow.sample() vs manual modulo approaches. Use when designing a vision pipeline that combines high-rate capture (30 fps+) with heavy per-frame work and you don't need every frame to be inferred.

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.

Scaffolds and configures a Vue 2.7 + Vuetify 2.7 frontend built with Vite 7 and Axios, with pinned versions, the vite.config.js alias and dedupe for Vue, the main.js bootstrap with new Vue and new Vuetify, MDI icons, VITE_ environment variables and an axios API module. Use when creating a frontend with Vite for a project that requires Vue 2 or Vuetify 2, migrating a Vue 2 app from Vue CLI to Vite, adding or upgrading dependencies in a Vue 2 project, setting up ESLint for Vue 2, or fixing errors such as Multiple instances of Vue detected, Vuetify is not properly initialized, or an npm peer conflict on vite.

Builds Vue 2.7 + Vuetify 2 screens with the correct v2 props, slots and events and with Vue 2 reactivity, for example a point-of-sale screen with product search, a table of editable sale lines, a total, a confirmation dialog, forms and snackbars. Covers v-data-table headers and item slots, v-autocomplete with server search, v-dialog activators, v-form validation, v-snackbar, custom v-model with value and input, and array updates with splice or $set. Use when writing or reviewing .vue components in a Vue 2 or Vuetify 2 project, when a Vuetify prop or slot seems to do nothing, when a table does not update after a change, or when porting a Vue 3 or Vuetify 3 example to Vue 2.

Use when the user asks to log work, record what was done, or save task progress. Creates a structured markdown task log in `agent-logs/` with validation, waivers, and a final gates summary.

Use when the user asks you to implement a feature, fix a bug, or complete a repository task end-to-end (from scoping through code changes, validation, and final gate summary).

Use when `.tf` or `.tfvars` files have been edited, added, or removed and you need to verify that the code changes produce the intended Terraform plan before the task is considered complete. Runs `terraform plan` in `examples/test_app` and cross-checks the result against the change set you expected your edits to cause. This is a gate: do not declare a Terraform task done without passing it.

Use when the user asks to write unit tests, generate a test suite, or migrate/convert Jest or Vitest tests to Themis in Node.js/TypeScript repos. Produces Themis-native tests, runs validation commands, and applies Themis migration workflows.

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.