--- title: "/cs-pm — Slash Command for AI Coding Agents" description: "Top-level project-management router. Classifies a PM inquiry across 8 lanes (sprint/flow, portfolio health, Jira, Confluence, admin, templates. Slash command for Claude Code, Codex CLI, Gemini CLI." --- # /cs-pm
Route this inquiry through the `pm-skills` orchestrator: **$ARGUMENTS** ## Routing (deterministic — run the script, don't eyeball) ```bash python3 project-management/skills/pm-skills/scripts/pm_goal_router.py --text "$ARGUMENTS" --output json ``` - Exit 0 → load `skill_path`/SKILL.md 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 — a saved Jira snapshot, retro log, or transcript resolves the lane silently. Never silently chain a second sub-skill. ## Output (≤200-word digest) - What was analyzed (with the data source — snapshot file, not memory) - Top 3 findings, each anchored to a canon citation - Top 3 next actions with a named human owner - Artifact path - One grill challenge (e.g. "Your health report is self-reported RAG — where's the derived diff that catches watermelons?") ## Hard rules - Flow numbers come from `jira_snapshot_bridge.py` on real snapshot data. - Forecasts are Monte Carlo percentile ranges, never single dates. - Live Jira/Confluence ops use only the tools in `project-management/references/atlassian-mcp-tools.md` — never invent tool names. - Goals (not questions) go to `/cs:pm-loop` instead. ## Distinct from - `product-team` — what to build. This domain is how to deliver it. - `/cs:harness` — the generic loop engine; `/cs:pm-loop` is its PM-domain adapter.