Skills
97,725 packaged capabilities and playbooks for agents. Install any of them with one command.
Agent workflows
Interview the user relentlessly about a plan, decision, or idea until reaching a shared understanding, using the agent's interactive question tool (not plain text). Use when the user wants to stress-test their thinking, clarify requirements, or says "grill me" or "query me".
Contextualizes an existing repository (brownfield) for AI-first work on it: verifies how to start and test it, creates the CodeGraph index, reconstructs the actual layer map, documents inherited decisions as ADRs, assembles the pattern catalog (canon vs. legacy), the debt map and verifiable build rules, all with file:line evidence, then pauses for human approval. Use when the ARCH role starts on an existing codebase without a PRD, or when asked to contextualize, onboard, document, map or understand a legacy/brownfield repository before working on it
Find the mistakes agents keep repeating in this repo and make each one impossible. Try architecture first, then types, then a lint whose error names the fix, then a test, and write docs last. Prove each check fails on a real past mistake. Repeat this each time the operator corrects you. Use for /correct.
End-to-end Course & Class Management coordinator. Guides teachers, lecturers, and instructors from RPS/RPP analysis, teaching module creation, tiered exercises, 16:9 slides, web and AR gamification, automated assignment assessment, OBE dashboards, portfolio reporting, through to textbook connections.
Operate Orca-managed worktrees, folder contexts, terminals, repos, automations, artifacts, skill sharing, worktree comments, and Orca's embedded browser through the `orca` CLI. Use when the user says "$orca-cli", "Orca worktree", "child worktree", "spawn codex/claude in a worktree", "read/wait/send Orca terminal", "handoff" / "handover" / "give this to another agent", "Orca browser", "orca artifacts", or "share skills". Prefer it over raw git worktree, ad hoc PTYs, or Computer Use when Orca state is involved. Use Computer Use only when a visible window needs GUI control that a CLI, filesystem, or API cannot do.
Align the current project's PRODUCT.md, DESIGN.md, GLOSSARY.md, and ARCHITECTURE.md after meaningful changes, and write the project Flow block on request. Use when the user says "update the docs", "sync the context", "keep the docs aligned", or "set up Flow here".
Use when a human wants to create, hire, activate, or set up a new AI employee from a plain-English description, e.g. wanting something that writes a weekly recap or replies to guest messages. Drives the Hiring Dozal's multi-turn setup wizard (the hiring chat), relays its button questions (show me first or just send it) to the human, and hires the finished Dozal. Use it for any new-employee request. Load operate-ai-employees first for auth and base-URL setup.
Use when a human wants to see, list, pause, reactivate, rename or inspect their existing AI employees (config, status active/paused/draft), or manage connected apps, schedules, handoffs, members and invitations, usage and bills, e.g. what employees do I have, pause the recap bot, how did last Friday go. Not for running one now (run-ai-employee), a task's output, approval or logs (monitor-and-review-ai-employee-work), or creating one (hire-ai-employee). Load operate-ai-employees first.
Use when a human asks whether an AI employee task is done, wants to see its output, or wants to approve or reject its work: is the recap ready, show me what it wrote, approve it, reject and shorten it, why did that run go wrong, show its logs, watch it live. Reads task status via phase_category, drives the approve/reject decision, and reads run logs, activity and live status. Load operate-ai-employees first for auth setup.
Use when a human asks you to operate their AI Employee platform account: hiring an employee, running one, checking on a task, approving or rejecting work, listing or pausing employees, or managing connections, schedules, handoffs, members, usage, bills, activity and run logs. Load this first to route between the four job skills. The umbrella skill: dze_ API key auth and its level, the production base URL, tenant resolution, the async model, and person-only steps.
Use the public `orca` CLI to operate Orca-managed worktrees, folder contexts, terminals, repos, automations, artifacts, worktree comments, and the browser embedded inside the Orca app. Use when the user says "$orca-cli", "use orca cli", "Orca worktree", "child worktree", "cardStatus", "spawn codex/claude in a worktree", "read/wait/send Orca terminal", "terminal send", "full handoff", "handover", "give this to another agent", "another worktree", "Orca browser", "orca artifacts", "share HTML/Markdown", "public artifact link", or "control the browser inside Orca". Prefer this over raw `git worktree`, ad hoc PTYs, Playwright, or Computer Use when the task touches Orca-managed state. Use Computer Use for browser windows, webviews, or desktop UI outside Orca's embedded browser.
Find where an agent pipeline can swap frontier models for cheaper ones without losing quality. Drive the installed rightmodeler TypeScript CLI through its resumable pipeline, interpret its machine protocol, present per-family verdicts, and open a reviewed model-swap pull request when the evidence supports one. Use when the user wants to cut model spend, right-size models per task, benchmark cheaper model substitutions, or analyze an agentic pipeline for cost optimization.
Use when a human wants to run, trigger, start, or test-run an existing AI employee, e.g. run the recap bot now, kick off the guest responder, or run it once per topic from a list of inputs. Triggers the employee, can dry-run to list required inputs, and hands back task handles without blocking. Load operate-ai-employees first for auth; use monitor-and-review-ai-employee-work to check the result.
Assess, set up, and verify how an AI development environment uses an organization's actual design system. Use when someone wants to keep AI on their system's rails, connect system knowledge and tools to coding agents, establish reuse and gap policies, or check whether those guardrails work. Focuses on the workflow and its evidence; ordinary page building or a full system inspection alone does not require this skill.
Use when work arrives at the software factory at any lifecycle stage — a new request, an informational question, a CI failure on a delivered PR, review findings, a merge notification, or a reply to a factory question — and must be routed to the right factory skill, human gate, or follow-up context.
Operate Orca-managed worktrees, folder contexts, terminals, repos, automations, artifacts, skill sharing, worktree comments, and Orca's embedded browser through the `orca` CLI. Use when the user says "$orca-cli", "Orca worktree", "child worktree", "spawn codex/claude in a worktree", "read/wait/send Orca terminal", "handoff" / "handover" / "give this to another agent", "Orca browser", "orca artifacts", or "share skills". Prefer it over raw git worktree, ad hoc PTYs, or Computer Use when Orca state is involved. Use Computer Use only when a visible window needs GUI control that a CLI, filesystem, or API cannot do.
Audit the skill inventory for quality, coverage, and staleness. Detect overlapping, incomplete, or outdated skills and produce a health report. Activate when: skill audit, stocktake, skill inventory, check skills, which skills exist, audit skills, skill quality, skill coverage.
Execute one bounded, already-decided work item — code, document, configuration, research artifact, Skill, or generic project task — by inspecting relevant context, offering agent-config routing when materially useful, verifying locally, and handing the result to review-loop with the appropriate specialist reviewer
Coordinate root Herdr orchestrators across the local server and enabled saved machines. Ask for their current work and progress, relay messages verbatim, and route task execution through workers. Pair with the shunk031-herdr-orchestrate-workers skill for worker dispatch. Use when one session oversees multiple Herdr orchestrators; use the herdr skill for a single-pane or single-agent task.
For Japanese writing and editing, decide whether to organize from the structure, locally refine AI-like wording while preserving the original meaning and strength of claims, concisely summarize business or technical documents, or turn content into an outline, telegraphic prose, or technical slides, then choose the appropriate skill. Use as an entry point for choosing a writing approach when asked to “write something,” “make it easier to read,” or “fix the AI-like tone.” Do not use for ordinary conversation or code-only editing requests.
Send an independent judge that is not the author: a fresh evaluator subagent that checks finished work against pass criteria written before it was built (evaluator mode), or audits a batch against its source of truth (audit mode), with evidence for every verdict and never a fix. Use when the owner asks for an evaluator, reviewer, auditor or judge, or says 'send a judge', 'evaluate this', 'check my work with a fresh agent', 'get a second agent to review this', 'audit this folder', 'audit my registry', 'verify this against the source of truth', or 'LLM-as-judge'. Runs only when asked; it does not fire on its own at the end of a task. Not for checks a machine can run (tests, schema validation, a search that must return zero), not for hundreds of identical units, and not for fixing anything.
Group a scope of Issues into Waves that can be implemented concurrently without stepping on each other — estimate what each Issue touches, exclude the ones that need a human, and print launch lines. Use when the user has several prepared Issues and wants to know which can run in parallel unattended
Hauptskill von Albatros: der Fluglotse. Fragt mit dem Werkzeug lage den echten Stand der Person ab (Abo, Schlüssel, Server oder Seite, Fliessband, Domain, Mission) und folgt dann genau dem Skill, der jetzt dran ist; nach jedem geschafften Schritt fragt er neu. Ohne Anmeldung zeigt er die offene Bibliothek aller Skills zum Selbstwählen und erklärt, wie die Anmeldung geht. Nutze den Skill, sobald jemand an seinem Albatros-Projekt weiterarbeitet oder fragt «was jetzt?», «wie weiter?», «was ist der nächste Schritt?», «wo stehe ich?», «es geht nicht», «es klemmt», «ich weiss nicht weiter», bei /albatros:lotse und am Ende des Skills start. Bei einer klaren Frage zu einem Thema (z. B. «wie verbinde ich meine Domain?», «was ist ein SSH-Schlüssel?») hat der passende Fach-Skill Vorrang.
Configure the Overextended skills. Picks which model and reasoning level each subagent role uses within a budget you choose, then detects your FiveM server, its ox resources and framework. Writes `~/.config/ox/models.md` and `.ox/config.md`, which the other ox skills read.
Runs shell commands in the background with a fire-and-forget approach and delivers progress notify turns every 2 minutes plus one notify turn to the agent session when each finishes, through the `agent-shell` command (a separate Bun project, installed to `~/.local/bin`). Use when a long command, build, test run or server must keep going without blocking the session, with the result read only after the completion notify turn arrives. Do not use for a quick command that finishes inside one turn.
Design and run a bespoke, auditable workflow for a task no narrower skill fits, such as a large migration, an ambitious multi-part change, or work the user reviews after stepping away. Scales rigor to the task, runs a hypothesis loop, and logs decisions. Use when the user asks you to figure it out, or for a large task no other workflow covers.
Delegate implementation work to external coding-agent CLIs (OpenAI Codex `codex exec`, Google Antigravity/Gemini `agy -p`, or any harness with an adapter) instead of Claude subagents, so heavy coding burns other providers' quota while Claude acts as foreman — planning, briefing, reviewing diffs and verifying. Use when the user invokes /foreman, asks to “use codex/gemini/agy as workers,” “save Claude quota/limits,” or “let another model do the coding while you review.” Workers run in isolated git worktrees via scripts/dispatch.sh.
Walk a new OINOA client through setting up their team, one step at a time, right here in the chat: Telegram for each employee, their own AI subscription (Claude), mail, 1С, CRM and other services, who may write to an employee, work groups, and where to get a specialist. Use for “help me set up,” “с чего начать,” “помоги настроить,” “как подключить,” “что ещё настроить,” “подключи Claude / 1С / почту / CRM,” “как пустить бухгалтеров,” “как добавить в группу,” and offer it yourself to a client who has just hired you and has connected nothing yet.
Keep a reviewable decision trail, a TSV log with one row per decision (what, why, evidence, result), for long-running, unattended or multi-phase work. Use when the user asks for a decision trail or will review the work after stepping away, or when a skill such as figure-it-out calls for it.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.