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description: Drive a project-delivery goal through a bounded agentic loop — Jira MCP snapshot → flow/sprint analytics bridge → routed sub-skill execution → machine-verified gates → close refused until everything is verified or human-waived. The PM-domain adapter over engineering/agent-harness. argument-hint: "<delivery goal, e.g. 'get sprint 14 to a verified close with health >= 70'>"

/cs:pm-loop — run a delivery goal to a verified close

Goal:

$ARGUMENTS

Sequence (gates are blocking — never skip forward)

1. Intake gate — the goal must name an observable outcome and its proof. If vague, run the /cs:grill-pm branches first (one question per turn). Do not loop on fuzz.
2. Observe — pull fresh data: mcp__atlassian__getAccessibleAtlassianResources (get cloudId) → mcp__atlassian__searchJiraIssuesUsingJql → save snapshot.json, then:

   python3 project-management/skills/pm-skills/scripts/jira_snapshot_bridge.py --input snapshot.json --to flow
   python3 project-management/skills/pm-skills/scripts/jira_snapshot_bridge.py --input snapshot.json --to sprint > sprint_data.json
   

3. Plan — write the task plan (owners, executors, reviewers, machine-checkable acceptance per task; shape via delivery_loop_gate.py --sample), then gate it:

   python3 project-management/skills/pm-skills/scripts/delivery_loop_gate.py --plan plan.json --mode plan
   

   Exit 2 → fix the listed G1–G4 violations before executing. For multi-task goals, compile through the repo harness instead (goal_compiler.py with the project-management.json manifest) and drive it with loop_controller.py.
4. Execute — one task at a time: route with pm_goal_router.py, run the routed sub-skill's own tools, record real exit codes and evidence. Retry means a changed approach; max 3 attempts per task.
5. Verify — the task's acceptance command must exit 0; sub-skill gates apply (scrum-master's ≥3-sprints rule, atlassian-admin's VERIFY steps). Never adjudicate your own verification; never edit a gate to make it pass.
6. Close —

   python3 project-management/skills/pm-skills/scripts/delivery_loop_gate.py --plan plan.json --mode close
   

   Exit 4 → close refused: finish, escalate, or get a human waiver (with reason). Exit 0 → report the handoff: tasks, statuses, evidence, waivers, and the flow-metrics before/after.

Rules

• Terminal states: success · clean no-op · blocked · approval-required · exhausted · stagnated. Exhausted budgets escalate to the named human — never reported as success.
• Jira writes are auditable: no transitionJiraIssue to Done without verify evidence; admin/destructive actions are approval-required, full stop.
• Max 12 loop iterations per goal; 3 attempts per task.