---
name: check-information-currency-with-latest-data
description: Old facts can send a customer or teammate down the wrong path.
category: Knowledge System Maintenance
stage: —
definitive_article: /knowledge-system-maintenance
status: needs-work
---

# Check information currency with latest data

Old facts can send a customer or teammate down the wrong path. This guide checks the claims that may have changed. Start with one page and the sources that can prove its facts today.

**The path:** Claims → Relevant sources → Current or stale → Repair handoff

**Start when:** The audit reaches its facts check, or new credible evidence may change a published claim.

## Inputs

- The current article revision, prior audit evidence and agreed scope.
- Access to relevant source systems: listing records, analytics/research exports, calls or campaign results when those claims occur.
- Official product documentation for current tool instructions and the authority for any source edits.

## Steps

1. List changeable claims with exact locations: dates, prices, counts, roles, screenshots, rankings and tool steps. Separate dated historical examples from claims about now.
2. For each claim, identify its strongest relevant source and required date range. The maintenance hub names Google Business Profile, Ahrefs, calls and campaign data as examples; do not require all four for a page that makes none of those claims.
3. Read the source and retain date, scope and evidence. Use current official docs for a provider’s controls. If access fails, mark not checked instead of inferring the value.
4. Mark each claim current, stale, contradicted or unknown. A newer page is not automatically more authoritative; compare the source’s role and what it actually measures.
5. Prepare narrow corrections to stale wording or screenshots. Preserve historical measurements as dated history rather than rewriting them as current results. Method changes require a reviewed [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).
6. Capture reusable new lessons through [Capture a lesson within 24 hours](https://local-service-spotlight.github.io/task-library/?task=generate-knowledge-capture-note-within-24-hours#task-generate-knowledge-capture-note-within-24-hours). Save the exact changed version, recheck affected claims after any authorized release, and report unresolved items with owners.

## Definition of done (QA checklist)

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

- [ ] Every in-scope changeable claim has a source and disposition.
- [ ] Historical facts and current facts remain distinct; inaccessible sources are unknown.
- [ ] Corrections and remaining gaps have saved evidence and a next owner.

## Example(s)

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

A fictional help page says a button is called Import. Current official help says Add files; a dated screenshot from last year still shows Import. Update the present-day instructions, label or replace the old screenshot, and keep the old run receipt unchanged. No campaign dashboard is needed for this UI-only claim.

## 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.

[Check links and their meaning](https://local-service-spotlight.github.io/task-library/?task=validate-cross-reference-integrity-across-articles#task-validate-cross-reference-integrity-across-articles) checks the changed page’s references, then [Record the audit result](https://local-service-spotlight.github.io/task-library/?task=update-status-table-in-definitive-article-guide#task-update-status-table-in-definitive-article-guide) records the combined audit result.

## 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=check-information-currency-with-latest-data#task-check-information-currency-with-latest-data)
- [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.