---
name: tag-proposal-with-affected-sop-and-queue-for-review
description: A good fix is easy to miss if it reaches the wrong list.
category: Knowledge System Maintenance
stage: —
definitive_article: /knowledge-system-maintenance
status: needs-work
---

# Tag proposal with affected task guide and queue for review

A good fix is easy to miss if it reaches the wrong list. This guide puts each proposal where its reviewer can find it. Start with the saved proposal and the guide it would change.

**The path:** Saved proposal → Format check → Exact guide tag → Reviewer queue

**Start when:** A saved process-change proposal needs a format check, exact guide tag and reviewer queue.

## Inputs

- [Draft a process-change proposal](https://local-service-spotlight.github.io/task-library/?task=create-sop-amendment-proposal-500-words#task-create-sop-amendment-proposal-500-words) output and the affected guide’s current canonical identity.
- The maintained proposal queue and a named reviewer with access.
- Submission source/time, priority and authority to update that queue.

## Steps

1. Read the whole proposal and count its body. Verify the four required parts and two real examples within 500 words; return gaps with a clear reason.
2. Tag the exact affected guide and section, keeping its canonical URL/source revision. A nickname or a similarly named article is not the correct target.
3. Check for an existing proposal about the same issue. Link related records or update the correct version without erasing the first submission time.
4. Add submitter, submission date, priority and current state. Split unrelated changes to different guides into linked proposals so each decision has a clear scope.
5. Place it in the approved review queue, ordered by genuine urgency then age. Record awaiting evidence or returned states honestly rather than calling every item ready.
6. Confirm the intended reviewer can read it and its private proof. Send any required notice only through existing authority. Keep the proposal queued until a real decision is recorded.

## Definition of done (QA checklist)

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

- [ ] Format/target checks are recorded; missing evidence is explicit.
- [ ] No duplicate proposal or overwritten history is introduced.
- [ ] Reviewer can reach the item and proof; actual state and date are accurate.

## Example(s)

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

A fictional proposal targets “the upload guide,” but two guides have similar names. The router reads both and tags the actual file-upload task with its source revision. One example link is private to the author; the item remains awaiting reviewer access, not ready for decision.

## 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.

[Review queued changes](https://local-service-spotlight.github.io/task-library/?task=senior-team-member-reviews-weekly#task-senior-team-member-reviews-weekly) receives the exact queued record, current source and evidence links.

## 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=tag-proposal-with-affected-sop-and-queue-for-review#task-tag-proposal-with-affected-sop-and-queue-for-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 `needs-work`. 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.