45 skills found
Creates detailed, sectionized implementation plans through research, stakeholder interviews, and multi-LLM review. Use when planning features that need thorough pre-implementation analysis.
Manage context-mode GitHub issues, PRs, releases, and marketing with parallel subagent army. Orchestrates 10-20 dynamic agents per task. Use when triaging issues, reviewing PRs, releasing versions, writing LinkedIn posts, announcing releases, fixing bugs, merging contributions, validating ENV vars, testing adapters, or syncing branches.
Use when building AI agent storage workflows on Tigris — forks for isolated dataset copies, workspaces for per-agent buckets with TTL, checkpoints for snapshot/restore, and coordination for event-driven pipelines via bucket webhooks. Triggers on "@tigrisdata/agent-kit", "agent storage", "agent workspace", "agent fork", "isolated agent environment", "checkpoint and restore", "bucket webhook", "multi-agent pipeline"
Simulate a collaborative dev team session where multiple role-based personas (PM, Architect, Developer, QA) respond to the same problem together in one session. Use when designing a feature, reviewing a proposal, or onboarding a new initiative and you want multi-role perspective without switching agents manually.
Use when the user asks for a code review by a fleet of specialized reviewer agents, wants multiple independent reviewer perspectives, or asks to run reviewers in single-pass or iterative fix-until-clean mode. Launches focused subagents for correctness, security, architecture, conventions, simplicity, UX, reliability, telemetry, testing, compatibility, and documentation review.
Fully autonomous research pipeline that turns a topic idea into a complete academic paper with real citations, experiments, and conference-ready LaTeX.
Use to extend an existing agent project with memory, app integration, VPC, multi-agent, migration, model, browser, code interpreter, payments, or resource removal. Triggers: "add memory", "remember across sessions", "call agent from app", "invoke agent from code", "agent auth", "streaming", "VPC", "VPC connectivity", "can't reach from VPC", "multi-agent", "A2A", "A2A auth", "orchestrator not delegating", "specialist not called", "migrate Bedrock Agent", "migration issue", "change model", "browse
AI Native Camp Day 4 Wrap & Analyze. session-wrap 스킬을 직접 만들고, history-insight와 session-analyzer로 세션을 분석한다. "4일차", "Day 4", "wrap", "세션 분석", "session wrap", "세션 래핑" 요청에 사용.
Create and manage agent graphs — directed graphs of configs connected by edges with handoff logic. Use when building multi-agent workflows where configs route to each other.
P9 Tech Lead mode — write Task Prompts, manage P8 agent teams, never write code yourself. Use when user says 'P9模式', 'tech-lead', '帮我管理这个项目', '任务拆解', or when coordinating 3+ parallel agents. Produces: Task Prompts (六要素) + P8 team delivery.
Activate when the user types `prose ...`, opens a `.prose.md` file with `kind:` frontmatter, opens a `.prose` file, or asks for reusable multi-agent orchestration. Treat `prose run ...` as an in-session instruction: embody the OpenProse VM yourself; do not shell out to a `prose` binary. On activation read the Markdown contract, select a state backend, wire responsibilities, execute with host primitives, and persist run state under the selected OpenProse root. Decline for one-shot questions — a p
Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases.
