Product Build Gate (hplan) + 5 agent-PM lifecycle plugins — 6 plugins, 43 skills, 18 commands for PMs who decide what, why, and how to build AI agents
This repository also configures its own agents. See what hplan tells them →
Plugin Claude Code
Bundles 4 skills · 259 tokens together
A set of guidance for designing AI-agent systems: software where several AI workers may coordinate to complete a task. It covers coordination patterns, business models, competitive advantages, and memory planning.
Plugin Claude Code
Bundles 10 skills, 1 command · 1,144 tokens together
Spec, build, and ship AI agents — PRD templates (prd --mode roadmap for roadmaps), instruction design, prompt engineering, sprint planning, context budget, stakeholder mapping, build-execution scaffolding (harness-design, parallel-team worktrees, build-loop), prompt-level progress tracking (velocity, estimate, blocker.
Plugin Claude Code
Bundles 6 skills · 560 tokens together
Discover which AI agent to build — map automation outcomes to solvable opportunities, validate assumptions, and decide build vs buy. Use when exploring agent ideas, analyzing automation opportunities, running build-or-buy analysis, or estimating agent development costs.
Plugin Claude Code
Bundles 8 skills, 11 commands, 4 agents · 1,565 tokens together
Evidence + COGS + Decision gate that runs BEFORE you commit to building. Mandatory competitor and interview evidence, executable COGS sentinel (p50/p90 margin with abuse blend), append-only Do-Not-Build exclusions registry, self-eval decision log, and multi-target handoff to Spec-Kit / Kiro / GStack / Claude Code. Use.
Plugin Claude Code
Bundles 6 skills · 494 tokens together
An operations toolkit for running AI agents in production. It organizes agent performance, reliability, costs, incidents, goals, and updates for stakeholders.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: