pfactory-watch

name	pfactory-watch
description	Poll one PFactory planning session through the pipeline and report where it stands — board column, gate result, blocking findings, and the readiness checks that still fail. One check per invocation, so it can be driven with /loop. Read-only; it never approves, waives, or emits.
when_to_use	After /handover-to-pfactory returns a session_id and you want to follow the session through enrich, feasibility and the review gates until it needs a human. Common triggers — "watch the pfactory session", "/pfactory-watch <session_id>", "is the plan reviewed yet", "did the gates pass", "/loop 30s /pfactory-watch <session_id>".
allowed_tools	["mcp__pfactory__plan_status","mcp__pfactory__plan_get","mcp__pfactory__plan_list","Read","Bash"]

/pfactory-watch

Poll one PFactory planning session and report its state. This skill does one check per invocation — to make it hands-off, run it under /loop:

/loop 30s /pfactory-watch <session_id>

/loop re-fires on the interval; the skill stops the loop as soon as the session reaches a state that needs a human or is finished.

Arguments

• session_id (required) — the id returned by /handover-to-pfactory. If omitted, call mcp__pfactory__plan_list and ask the user which session to watch.

Procedure (one pass)

Step 1 — poll

mcp__pfactory__plan_status(session_id: "<id>")

Read: status, board_state, gates_passed, needs_human, correlation_key, issue_number, aifactory_task_id.

Step 2 — classify

Bucket	status	Action
Running	ingested, processing, reviewing	print a one-line progress update (status / board_state) and let the loop re-fire
Needs a human	processed (board human_review)	go to Step 3, then STOP the loop
Rejected	rejected	report the approver's feedback, then STOP the loop
Done	approved, emitted	report the outcome (Step 4), then STOP the loop

processed means the AI work is finished and the session is parked in human_review awaiting sign-off — that is the normal terminal state for this skill. Approval is a human act, so never call plan_approve from the loop.

To stop the loop, finish the turn without scheduling another iteration and say plainly that the session is terminal.

Step 3 — report the review

Call mcp__pfactory__plan_get(session_id) and summarise:

1. gates_passed, the aggregate score, and the per-lens scores (architecture, security, best-practice, feasibility).
2. Blocking findings, each with its citation — a finding restated without its citation is not reportable.
3. The feasibility estimates: coarse cost, effort rollup, IAM access decisions.
4. Every hard readiness check that failed, by name (children-present, criteria-present, ac-child-coverage, deps-sound, access-granted, env-buildable, enrichment-integrity, language-reconciled, change-footprint-surfaced, constitution-grounded, deployment-pipeline-present, no-blocking-findings, decompose-trustworthy). A plan cannot be approved while any of these is failing and unwaived; no-blocking-findings can never be waived.
5. The concrete next step for the user: approve, fix the plan and re-ingest, or record a waiver. Present it, do not act on it.

Step 4 — on approved / emitted

• approved — gates passed and a human signed off. The next step is emit (/handover-to-pfactory Step 6), which is dry-run by default.
• emitted — report issue_number, correlation_key and aifactory_task_id so the user can follow the work into AIFactory and TFactory under one key.

Notes

• Strictly read-only. plan_status / plan_get / plan_list have no side effects; this skill never approves, waives, rejects or emits.
• Cadence: 30s is a good default. plan_process does live-cloud enrichment, reconnaissance and LLM review lenses, so a session can sit in processing or reviewing for minutes.
• Host without MCP: GET /api/plan/sessions/{id} returns the same view. See guides/agent-handoff.md.
• Pairs with /handover-to-pfactory — that skill hands the plan over and returns the session_id; this one follows it to the human gate.