openrig skills

Use when opening OpenRig fleet terminals as a herdr wall — turning a rig, pod, mission, slice, or saved view into live interactive agent tiles via `rig terminal`, watching another rig read-only, or driving herdr on an agent's request ("open all my rigs + a mission as views"). Covers the `rig terminal open|views|status` verbs, the honest-partial/degrade reading of the result, the read-only-by-construction rail for cross-rig views, scroll/copy out of the box, and the same-size-only duplicate-pane limit. herdr is the default, proof-gated provider.

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

Use when opening OpenRig fleet terminals into cmux — turning a rig, pod, mission, slice, or saved view into live agent tiles via `rig terminal --provider cmux`, or driving cmux on an agent's request. Same OpenRig view semantics as openrig-herdr (the verbs, honest-partial/degrade, read-only cross-rig, scroll/copy, same-size-only duplicates); cmux is the **best-effort** provider (herdr is the default and the proof-gated one). Prefer openrig-herdr unless cmux is specifically wanted.

Use when a development pod begins or hands off implementation, QA, or design work.

Use when changing OpenRig's own source in a clone of the openrig repository: finding which package or file owns a behaviour, choosing which tests to run, testing a change without disturbing the OpenRig daemon your own session runs on, judging whether a diff touches a high-risk area, or preparing a pull request. Not for operating rigs (openrig-skills) or designing rig topologies.

Use when an agent is preparing or performing an OpenRig CLI/daemon upgrade and must preserve live seats, verify each mutation, or reconcile managed plugin and skill files without overwriting local work.

Use when you're operating OpenRig and need the right skill or context for fleet recovery, seat handover, new-seat orientation, a watchdog wake, cross-host reach to an agent on another machine, rig packaging, an OpenRig upgrade, systematic debugging, queue triage, or implementation planning; also use when you don't know what applies or nothing is projected on cold boot.

Use when creating, refreshing, packaging, inspecting, promoting, or deprecating a named per-seat starting point — Agent Starter manifest authoring, the 6-state lifecycle (captured → named → inspectable → used → promoted → deprecated), provenance honesty, and refusal rules. NOT a VM image; a managed starting point composed from agent role + startup context + optional native session source + provenance.

YC-style product validation using six forcing questions. Pressure-tests a feature idea before it becomes a requirement — ensuring real demand, a clear wedge, and evidence behind assumptions.

Create UI mockups at three fidelity levels — ASCII wireframes for quick iteration, standalone HTML mockups for delivery with requirements, and live prototypes for interaction testing.

Use when coordinating assignments, selected review boundaries, or blocked work across a rig.

Use when implementing any feature or bugfix, before writing implementation code

Use when designing, reviewing, or debugging how an agent's context window gets filled, pruned, or shared — choosing what loads at boot versus on demand, sizing an install or an always-loaded file, fixing an agent that drifts, repeats itself, or forgets constraints mid-task, planning compaction or summarization, deciding single-agent versus subagents, engineering handoffs between agents, or picking a tool loadout. NOT for rewording a prompt's tone, choosing which model to pin, or debugging business logic — those are adjacent moments this skill does not serve. Historical 2024–2025 snapshot; not normative for present-day frontier models — see the Status section.

Use when addressing a registered remote OpenRig host, choosing its transport, or interpreting a cross-host result.

Use when authoring or installing a rig bundle (packaged, shareable artifact that instantiates an opinionated OpenRig topology + workflow), reasoning about the bundle vs extension boundary, or auditing a bundle for portability. Covers the 4 failure modes that prevent bundles from working anywhere but the operator's machine, and the inspect-before-install discipline.

Use when authoring rig specs, agent specs, workflow specs, startup/context fragments, operating-mode declarations, or designing the user spec library. Covers the 4 failure modes (spec instantiates topology but not workflow/mode; spec depends on local paths and fails on another host; agents modify specs as one-off files instead of preserving reusable intent; validation proves YAML shape but not whether topology can run) and the validation-vs-runtime-realization distinction.

Quickly capture product ideas, feature requests, or insights from meetings and conversations. Rapid documentation with smart categorization and deduplication.

Use when project policy calls for a human decision or update, a human delivery is pending or failed, or a reply must resume the right work.

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.

Use when classifying a slice closeout (auto-continue / human gate / park), routing a real decision to a human, or designing a human queue/dashboard surface. Treats humans as durable network participants with attention surfaces, queues, and decision records — escalation lands as a durable attention item, not a chat message. Approval is NOT required for every clean closeout; the default RSI conveyor continues unless an explicit human gate is reached.

Gather and distill context from meetings, competitors, regulatory sources, and internal discussions. Produces background.md for a feature and updates shared context docs when new knowledge is discovered.

Use when assigned a review or when an authored review boundary is reached.

Use when you are a seat on the oversight pod (a standing monitor-mode rig that keeps OTHER rigs healthy), configuring or running the drift detectors, or choosing whether to intervene vs escalate. Covers the pull-not-poll posture, the v0 detectors (premature-park, process-drift, off-task, token-burn), the intervention ladder (orchestrator-ping -> refocus -> human escalation), and the cheap+deep model economics. NOT for orchestrating your OWN rig (orchestration-team) and NOT the intervention primitive mechanics (watchdog).