---
name: review-past-6-months-of-sop-amendment-proposals-for-patterns
description: Repeated fixes can show where a guide needs more work.
category: Knowledge System Maintenance
stage: —
definitive_article: /knowledge-system-maintenance
status: needs-work
---

# Review past 6 months of task guide Amendment Proposals for patterns

Repeated fixes can show where a guide needs more work. This task looks across past change requests for the cause. Start with the real records for a clear six-month period.

**The path:** Complete period → Distinct proposals → Checked patterns → Owned actions

**Start when:** The system review needs a source-backed pattern report for its stated six-month period.

## Inputs

- The proposal tracker export for an explicit six-month period, including returned/rejected items.
- Related guide versions, review dates and a prior-period export if one exists.
- The maintenance process map and a reviewer for the analysis.

## Steps

1. Record the exact time window and export coverage. Include all known states; list missing records and tests separately. Deduplicate versions by proposal ID instead of counting each edit as a new request.
2. Classify each real proposal by affected guide, problem type and outcome. Retain the source and decision evidence for each classification.
3. Calculate proposals per guide; approved divided by decided proposals for approval rate; and median elapsed submission-to-decision time for records with both dates. State denominators, excluded missing dates and open proposals.
4. Compare with a prior period only when definitions and coverage match. Do not turn a larger collected sample into a growth claim.
5. Investigate repeated guide changes, missing-process clusters and returned-format patterns. Zero proposals may reflect low activity, good methods, missing capture or queue friction; test the possibilities before calling it failure.
6. Give each supported pattern a specific proposed action, owner and evidence. Keep uncertain explanations as questions. Feed method changes through [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).

## Definition of done (QA checklist)

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

- [ ] Distinct real proposals and coverage are reconciled; samples/versions are excluded.
- [ ] Metric formulas, denominators and missing data are visible.
- [ ] Each supported pattern has an owner and next action, without automatic cause claims.

## Example(s)

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

A fictional export contains 8 real proposals: 4 approved, 2 rejected and 2 pending. Approval rate among decided proposals is 4/6, not 4/8. Two approved proposals concern the same confusing field, so the review proposes a field-definition fix. The eight proposals do not establish eight completed client jobs.

## 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.

[The six-month system review](https://local-service-spotlight.github.io/task-library/?task=audit-this-maintenance-article-every-6-months#task-audit-this-maintenance-article-every-6-months) receives the pattern report, evidence and unresolved questions.

## 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=review-past-6-months-of-sop-amendment-proposals-for-patterns#task-review-past-6-months-of-sop-amendment-proposals-for-patterns)
- [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.