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Turn project issues into execution-ready, wave-organized implementation plans with risk prediction, specialist agent assignment, and TDD workflow integration.
Wave Planner ingests project issues from PM tools (GitHub, Linear, Jira), groups them into execution waves, surfaces architecture decisions, predicts risks and blockers, and generates execution-ready artifacts (plans, ADRs, hive configs). It also estimates token budgets and assigns specialist agents to tasks, producing a structured, reviewable plan ready for execution.
Use Wave Planner when you need to convert a backlog or project issue set into an actionable rollout: sprint/wave-by-wave implementation planning, pre-release architecture decision capture, risk analysis before large changes, or when coordinating multiple specialist agents across a cross-functional delivery. Invoke explicitly (e.g. /wave-planner) or by natural language triggers such as: plan the implementation, break down the API redesign into waves.
Agent runtimes supporting task orchestration and shell access (Claude-style agent flows, agentic LLM runners that provide Read/Write/Edit/Bash tools).
Wave Planner is a project planning skill that transforms PM tool issues (Linear/GitHub/Jira) into wave-organized implementation plans with risk analysis, specialist agent assignment, and TDD workflow integration. The SKILL.md is well-structured with progressive disclosure into sub-files (preflight.md, execution.md, reference.md). No scripts were bundled, so no execution testing was possible. The skill requires a specific ecosystem (claude-flow, hive-mind, Linear CLI, Docker) which limits broad applicability.
Clean skill with no security concerns. Env var examples use clearly placeholder values (lin_api_xxx, ghp_xxx). Well-decomposed architecture with good progressive disclosure. Niche usefulness due to heavy dependency on specific tooling ecosystem.
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