/cs-product
Top-level product-team router. Classifies a product inquiry across 16 lanes (prioritization, OKRs, UX, design system, competitive, analytics, experiments, discovery, roadmaps, spec-to-repo, landing, SaaS scaffold, stories, HIG, code-to-PRD, summarizer) with a deterministic
$ npx -y skills add alirezarezvani/claude-skills --agent claude-codeHow it fires
How this command gets triggered: by you, by Claude, or both.
- Fires itselfClaude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/cs-product
Context preview
What this command does when you run it.
Top-level product-team router. Classifies a product inquiry across 16 lanes (prioritization, OKRs, UX, design system, competitive, analytics, experiments, discovery, roadmaps, spec-to-repo, landing, SaaS scaffold, stories, HIG, code-to-PRD, summarizer) with a deterministic
Command definition
cs-product.mddescription: Top-level product-team router. Classifies a product inquiry across 16 lanes (prioritization, OKRs, UX, design system, competitive, analytics, experiments, discovery, roadmaps, spec-to-repo, landing, SaaS scaffold, stories, HIG, code-to-PRD, summarizer) with a deterministic script and forks context to the right sub-skill via the product-skills orchestrator, returning a ≤200-word digest with one grill challenge.
argument-hint: "<product inquiry: prioritize features, plan an experiment, discovery health, etc.>"
/cs:product — Product Team router
Route this inquiry through the `product-skills` orchestrator:
**$ARGUMENTS**
Routing (deterministic — run the script, don't eyeball)
python3 product-team/skills/product-skills/scripts/product_goal_router.py --text "$ARGUMENTS" --output json
- Exit 0 → load `skill_path`/SKILL.md (covers the 4 standalone plugins too) and follow
that skill's own workflow in a fork.
- Exit 2 → ask ONE clarifying question naming the listed candidates, recommended answer
first.
- Exit 3 → ask the user to restate the goal with the deliverable named. Never guess.
- Explore the workspace first — an `ost.json`, `discovery_log.json`, or `features.csv`
resolves the lane silently. Never silently chain a second sub-skill.
Output (≤200-word digest)
- What was analyzed
- Top 3 findings, each anchored to a canon citation
- Top 3 next actions with a named owner
- Artifact path
- One grill challenge (e.g. "This roadmap cites an OST that fails the linter — which
opportunity backs item 3?")
Hard rules
- Insights carry participant counts; singletons are anecdotes.
- Experiments carry computed sample size + MDE, never gut feel.
- Prioritization names its framework (RICE / WSJF / opportunity score) and why.
- AI features get an eval spec (golden set + rubric + guardrails) in the PRD.
- Recurring discovery work goes to `/cs:product-loop` instead.
Distinct from
- `project-management` — how to deliver. This domain is what to build.
- `marketing/landing` — from-scratch marketing pages; `landing-page-generator` here
scaffolds product Next.js/TSX pages.
Read more
description: Top-level product-team router. Classifies a product inquiry across 16 lanes (prioritization, OKRs, UX, design system, competitive, analytics, experiments, discovery, roadmaps, spec-to-repo, landing, SaaS scaffold, stories, HIG, code-to-PRD, summarizer) with a deterministic script and forks context to the right sub-skill via the product-skills orchestrator, returning a ≤200-word digest with one grill challenge. argument-hint: "<product inquiry: prioritize features, plan an experiment, discovery health, etc.>"
/cs:product — Product Team router
Route this inquiry through the `product-skills` orchestrator:
**$ARGUMENTS**
Routing (deterministic — run the script, don't eyeball)
python3 product-team/skills/product-skills/scripts/product_goal_router.py --text "$ARGUMENTS" --output json
- Exit 0 → load `skill_path`/SKILL.md (covers the 4 standalone plugins too) and follow
that skill's own workflow in a fork.
- Exit 2 → ask ONE clarifying question naming the listed candidates, recommended answer
first.
- Exit 3 → ask the user to restate the goal with the deliverable named. Never guess.
- Explore the workspace first — an `ost.json`, `discovery_log.json`, or `features.csv`
resolves the lane silently. Never silently chain a second sub-skill.
Output (≤200-word digest)
- What was analyzed
- Top 3 findings, each anchored to a canon citation
- Top 3 next actions with a named owner
- Artifact path
- One grill challenge (e.g. "This roadmap cites an OST that fails the linter — which
opportunity backs item 3?")
Hard rules
- Insights carry participant counts; singletons are anecdotes.
- Experiments carry computed sample size + MDE, never gut feel.
- Prioritization names its framework (RICE / WSJF / opportunity score) and why.
- AI features get an eval spec (golden set + rubric + guardrails) in the PRD.
- Recurring discovery work goes to `/cs:product-loop` instead.
Distinct from
- `project-management` — how to deliver. This domain is what to build.
- `marketing/landing` — from-scratch marketing pages; `landing-page-generator` here
scaffolds product Next.js/TSX pages.
362 production-ready Claude Code skills, plugins, and agent skills for 13 AI coding tools. The most comprehensive open-source library of Claude Code skills and agent plugins — also works with OpenAI Codex, Gemini CLI, Cursor, and 9 more coding agents.
Repo: alirezarezvani/claude-skills
Other commands on claude-skills.
- /focused-fix
Deep-dive feature repair — systematically fix an entire feature/module across all its files and dependencies. Usage: /focused-fix <feature-path>
Open command - /clean
Clean up merged branches locally and on remote, keeping only main, dev, and gh-pages.
Open command - /cm
Stage working tree changes and create a Conventional Commit (no push).
Open command - /cp
Stage, commit, and push the current branch following git governance rules.
Open command - /pr
Create a pull request from the current branch.
Open command - /plugin-audit
Comprehensive audit pipeline for skills, plugins, agents, and commands. Validates structure, quality, security, marketplace compliance, cross-platform compatibility, and ecosystem integration. Runs all built-in validation tools, invokes domain-appropriate agents for code review,
Open command

