---
name: schedule-first-6-month-recursive-review
description: Your guide system needs a date to check itself.
category: Knowledge System Maintenance
stage: —
definitive_article: /knowledge-system-maintenance
status: gap
---

# Schedule first 6-month recursive review

Your guide system needs a date to check itself. This task sets up that first review with the right people and records. Start with when the system was adopted and who owns it.

**The path:** Adoption date → Review owners → Saved agenda → Verified handoff

**Start when:** No checked first system-review plan exists, or its adoption date and ownership need reconciliation.

## Inputs

- Evidence of the maintenance system’s actual adoption date and any existing review schedule.
- A review lead, approving reviewer, availability and timezone.
- The audit register, proposal tracker, capture records and portability-review locations.

## Steps

1. Check for an existing review event or job and its owner before creating another. Preserve it if it already meets the need.
2. Use six months from documented adoption as the first planning date. If adoption is unknown, ask the owner to set a transparent baseline; do not invent it or backdate an event.
3. Agree the real review date and participants. Record a separate preparer if exports need advance work.
4. Build an agenda: first analyze the proposal history, then audit the maintenance article and its five processes, then agree the next cycle. Attach source locations and required evidence periods.
5. Save through the authorized calendar/task system. Read back date, timezone, recurrence if any, participants and agenda link. Confirm availability or leave acceptance pending.
6. Record the scheduled state in the maintained audit system. Assign prep collection and the later review; this setup task does not claim the meeting has happened.

## Definition of done (QA checklist)

[Quality assurance (QA)](https://localservicespotlight.com/article-guidelines/) means checking the work against the agreed result.

- [ ] Date is based on a real adoption record or an explicitly agreed new baseline.
- [ ] Named reviewers can access the saved agenda and evidence list.
- [ ] Existing schedules are reconciled; scheduled, accepted and held are distinct states.

## Example(s)

**Fictional teaching example. This is not a client result or proof of a completed run.**

A fictional system was adopted on 10 January, making 10 July the six-month point. One reviewer is unavailable that day; the team agrees 12 July and records the reason. If the event is saved but the second reviewer has not replied, acceptance remains pending. No six-month audit is counted.

## Handoff and Content Factory context

This work supports the [Content Factory, our four stages of using real content](https://blitzmetrics.com/content-factory/): Produce → Process → Post → Promote. Use the specific inputs and next task below to place the work; a maintenance task does not manufacture transcripts, clips or other stage outputs it does not call for.

[Prepare the pattern review](https://local-service-spotlight.github.io/task-library/?task=review-past-6-months-of-sop-amendment-proposals-for-patterns#task-review-past-6-months-of-sop-amendment-proposals-for-patterns) feeds [the actual maintenance audit](https://local-service-spotlight.github.io/task-library/?task=audit-this-maintenance-article-every-6-months#task-audit-this-maintenance-article-every-6-months).

## Run with an agent

Give the AI worker this recipe, the real Inputs above, the intended result and the actions already authorized. Ask it to return the saved output, checks, evidence and remaining owner. Check its work against this guide; loading a skill does not prove access, installation of a job, or successful execution. Keep media muted with volume at zero if playback is needed.

For recurring work, keep the actual trigger, owner and runtime in the job record. Scheduling and observed firings are separate. Do not create a schedule merely because this guide mentions a review interval.

## Record the real execution

Open the run record when the work starts. Keep the exact starting recipe revision, one execution ID, source evidence and actual state. Write a [meta article, the record of one run](https://blitzmetrics.com/meta-article-prompt/) with decisions, results, checks, failures and next owner. Link it to this task and register it through the [Task Library](https://local-service-spotlight.github.io/task-library/) execution process. Writing is part of the work; public release follows existing authority.

Reuse the same execution ID for revisions, QA, meta writing and retries within that run. A blocked run stays open with its dependency and next owner; do not invent a finish time. Use supported findings to propose and verify a better recipe. A historical public-example count without distinct run IDs remains dated article volume, not verified execution frequency.


<!-- factory-layer:start -->

## Factory chain (do not treat this as isolated)

- **Phase:** —
- **Importance:** 2/5 `●●○○○` — frequency 2, revenue 1, gating 2 (supporting)
- **Suggested previous station:** —
- **Suggested next station:** —
These stations are generated neighbors, not verified prerequisites or handoffs. Follow the task’s actual Inputs and Handoff sections.
- **Handoff:** Save this task’s actual output, source, date and checks where the receiving owner can read them. Follow the Inputs and Handoff sections for its next step.

## Model routing (same factory, any engine)

- **This task's lane:** `any` — Any capable chat model (Claude, ChatGPT, Grok, Gemini). SOP following, drafts, checklists.
- **Single-engine path:** Use the capable AI app you already have. Check its required tools and access before starting. Pass the actual result and proof to the next task.
- **Optional multi-engine:** A tested local model may draft; a stronger model may review facts and voice. Use supported tools for approved actions. Pick models from observed quality and cost; a model name does not prove it can run this task.
- **Never** store the working state in one vendor's memory. Files in the Content Library are the bridge.

<!-- factory-layer:end -->
## Definitive article & links

- [Maintained source guide](https://blitzmetrics.com/knowledge-system-maintenance/)
- [This task in the Task Library](https://local-service-spotlight.github.io/task-library/?task=schedule-first-6-month-recursive-review#task-schedule-first-6-month-recursive-review)
- [Article Guidelines](https://localservicespotlight.com/article-guidelines/)
- [current article guide](https://blitzmetrics.com/definitive-article-guide/)
- [How recipes and run records work together](https://localservicespotlight.com/meta-articles/)

## Review and evidence still needed

The inherited contributor status is `gap`. It is preserved, not promoted by this rewrite. That label alone does not verify document readiness, a client outcome, access or an executed task.

A real execution still needs its own source, reviewer, saved result and handoff evidence. The fictional example teaches the method; a real example with relevant proof is still needed where required. The task-specific flow above is source guidance; its visible presentation and the full document need a named reviewer and desktop/mobile checks.