Artawower

Проведение ревью и анализ результата через независимого агента...

Describe the current jj revision with a proper commit message. Use when the user wants to create a commit message, describe changes, write a commit summary, prepare a commit description, or says "describe this revision", "what should I commit", "create commit message".

Coordinate a local multi-agent coding team via pi-link. Use when the user wants a real team lead who decomposes work, assigns roles (researcher, coder, reviewer), manages execution order, or asks to orchestrate multiple agents safely.

Helps describe changes clearly, follow conventional commit style, keep jj revisions focused, and apply agent/skill creation best practices. Use whenever the user asks how to name a change, write a commit or revision description, decide whether to reuse the current jj revision, create or modify an agent or skill, or wants cleaner change hygiene before editing files.

Reviews uncommitted changes or an explicitly requested diff with a strict KISS/DRY/SOLID rubric. Use when the user asks for a code review, diff review, pre-commit validation, or a quality pass on recent changes.

Runs an independent multi-model review of the current diff, stores per-model reports, merges duplicates, and produces a skeptical consolidated verdict in Russian. Use when one reviewer is not enough and the user wants crowd wisdom.

Use context-mode tools (ctx_execute, ctx_execute_file) instead of Bash/cat when processing large outputs. Triggers: "analyze logs", "summarize output", "process data", "parse JSON", "filter results", "extract errors", "check build output", "analyze dependencies", "process API response", "large file analysis", "page snapshot", "browser snapshot", "DOM structure", "inspect page", "accessibility tree", "Playwright snapshot", "run tests", "test output", "coverage report", "git log", "recent commits", "diff between branches", "list containers", "pod status", "disk usage", "fetch docs", "API reference", "index documentation", "call API", "check response", "query results", "find TODOs", "count lines", "codebase statistics", "security audit", "outdated packages", "dependency tree", "cloud resources", "CI/CD output". Also triggers on ANY MCP tool output that may exceed 20 lines. Subagent routing is handled automatically via PreToolUse hook.

Show how much context window context-mode saved this session. Displays token consumption, context savings ratio, and per-tool breakdown. Trigger: /context-mode:ctx-stats

Delegate deep domain analysis, architecture planning, or complex decisions to your own scope's expert agent (claude-opus). Ensures the expert is running for YOUR scope. Use for architectural decisions, multi-step planning, tradeoff evaluation, domain modeling. Never borrows agents from other scopes.

Full feature development cycle with herdr-managed agent panes. Ensures an ai-workers tab exists with coder, researcher, and critic panes, then orchestrates implement-review loop via pi-link. Use when you want a persistent multi-agent workspace managed by herdr.

Delegate a research task to your own scope's researcher agent. Ensures ai-workers panes are running for YOUR scope, then sends the request to <scope>@researcher. Use for codebase exploration, external references, pattern lookup. Never borrows agents from other scopes.

Delegate a code review to your own scope's critic agent. Ensures ai-workers panes are running for YOUR scope, then sends the request to <scope>@critic. Use for code review, diff review, quality checks. Never borrows agents from other scopes.

Analyze colleague feedback for relevance, objectivity, and practical value. Use when evaluating code review comments, architectural feedback, or any critique from a peer before deciding what to act on.

Full feature development cycle with multi-agent collaboration — researcher, coder, and reviewer. Use when implementing a non-trivial feature that benefits from research, iterative coding, and independent review.

Delegate a task to the most suitable connected agent via link_prompt and return the result to the user. Use when you want to route a request to a specialist colleague on the pi-link network.

Request a code review from an independent reviewer agent via link_prompt, then analyze and act on the findings. Use when you want an external perspective on recent changes before committing or merging.

Анализ замечаний коллеги на релевантность, объективность и практическую ценность.

Полный цикл разработки фичи с последующей проверкой и дискуссией для повышения качества за счёт коллаборативной работы нескольких агентов.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Делегирует задачу подходящему коллеге через link_prompt и возвращает результат пользователю.

Reviews CSS/SCSS changes in the current branch for over-specificity, missed reuse opportunities, and over-engineered abstractions. Produces analysis findings and uses pm7y-ralph-planner to generate TASKS.md for autonomous execution. Use when reviewing CSS changes before commit or PR, or to audit existing styles. Supports @file syntax to target specific files.

jj revision hygiene for pi. Use in jj repositories — check revision scope before writing, run jj new for unrelated work, describe revisions after changes.