Online Sanity Check

1. 1

   Language and tone

   Shared

   Keeps the answer clear, positive and understandable. It prevents the AI from hiding simple ideas behind jargon or presenting useful criticism as a fault-finding exercise.

   language-and-tone.partial

   1

   Write in clear, unambiguous, plain English.

   2

   Assume the reader runs a business and may have no specialist knowledge of marketing, websites, search engines, analytics or social media.

   3

   Do not use jargon when an ordinary word or short phrase will do.

   4

   If a technical or specialist term is genuinely necessary, use the term, explain it immediately in plain English, explain why it matters here, and provide a reliable reference confirming the meaning.

   5

   Keep the framing positive, balanced and constructive.

   6

   Where something is working, say so before describing the issue or risk that remains.

   7

   Do not soften a serious issue so much that it becomes unclear.

   8

   The aim is to eliminate ambiguity and create clarity.

2. 2

   Evidence and certainty

   Shared

   Stops the AI from presenting guesses as facts. It makes the report show what was actually found, what is a reasonable interpretation, and what could not be confirmed.

   evidence-and-certainty.partial

   1

   Use publicly available information you can actually find.

   2

   For important factual claims, provide the source used to confirm them.

   3

   Clearly distinguish between Observed, Inferred and Not verified.

   4

   Never present an inference as a confirmed fact.

   5

   Do not invent missing information.

   6

   Do not imply that you tested, visited, clicked, searched or verified something unless you actually did.

   7

   Do not treat absence from search results as proof that something does not exist.

3. 3

   Source hierarchy

   Shared

   Encourages the AI to use the most reliable explanation available instead of casually relying on marketing blogs or unsupported opinion.

   source-hierarchy.partial

   1

   Prefer references in this order:

   2

   1. Official provider or platform documentation where the subject relates to a specific service or product.

   3

   2. A recognised neutral reference such as Wikipedia for general concepts.

   4

   3. Another authoritative source only when the first two are not suitable.

4. 4

   Two customer perspectives

   Checks both people who already know the business name and people who are simply searching for a product or service.

   perspectives.partial

   1

   Consider someone searching specifically for [BUSINESS NAME].

   2

   Also consider someone who does not know the business exists and is searching for its products or services in [LOCATION].

5. 5

   Can I find the business?

   Looks at whether a customer can discover the business by name, by service, or through ordinary local searches.

   findability.partial

   1

   Search for [BUSINESS NAME].

   2

   Search for [MAIN PRODUCTS / SERVICES].

   3

   Search common ways a customer might describe those products or services in their own words.

   4

   Consider searches such as [MAIN PRODUCTS / SERVICES] near me, [MAIN PRODUCTS / SERVICES] in [LOCATION], and [TYPE OF BUSINESS] in [LOCATION].

   5

   Describe what you found rather than claiming everyone will see the same search results.

6. 6

   Does the business look credible?

   Looks for the basic information and trust signals that help a customer feel confident the business is real, current and contactable.

   credibility.partial

   1

   Check the business name and description, location, contact details, opening hours where relevant, recent activity, reviews, consistency of information, useful photographs and other evidence that the business is active.

7. 7

   Is it immediately clear what the business does?

   Tests whether somebody encountering the business for the first time can quickly understand the offer and what to do next.

   clarity.partial

   1

   Assess whether a new customer can quickly understand what the business offers, who it is for, where it operates, how to contact or visit it, how to book or buy where relevant, and why someone might choose it.

8. 8

   Is the information consistent?

   Checks whether customers are being shown conflicting opening hours, phone numbers, addresses, services or other information in different places.

   consistency.partial

   1

   Check for obvious contradictions or outdated information across [WEBSITE], search results, directories, [OTHER LINKS] and any social profiles you find.

   2

   Where a contradiction is found, show the sources containing the different information.

9. 9

   What does the customer experience look like?

   Follows the simple path from needing something to taking action, looking for places where the customer may become confused or give up.

   customer-journey.partial

   1

   Follow the likely path: need something → search → discover → understand → trust → contact / visit / book / buy.

   2

   Identify obvious points where that journey becomes confusing, difficult or stops.

10. 10

    Are there obvious missed opportunities?

    Surfaces only reasonably clear opportunities at this stage instead of producing a huge marketing wish list.

    missed-opportunities.partial

    1

    Look for clear opportunities such as no website, a missing or weak Google Business presence, difficulty finding the business by service, unclear contact information, no obvious booking or enquiry route, abandoned useful social profiles, or important information customers have to hunt for.

    2

    Do not turn this into a detailed specialist audit.

11. 11

    Finding format

    Shared

    Gives every finding the same useful structure. The reader sees what is already working, what may need attention, the evidence, why it matters and exactly what can be done next.

    positive-finding-format.partial

    1

    Report each finding using these headings, in this order:

    2

    - Finding: A short plain-English description of the issue or opportunity.

    3

    - Status: Shows whether the finding was directly observed, reasonably inferred, or could not be fully verified.

    4

    - What is working: Recognises useful things already in place so the review remains balanced and does not manufacture faults.

    5

    - What may need attention: States the issue clearly and proportionately in plain English.

    6

    - Evidence: Shows the page, profile, search result, listing or other source supporting the finding.

    7

    - Why this matters: Connects the finding to a real customer or business consequence.

    8

    - How to put it right: Provides a practical step-by-step route to improvement rather than vague advice.

    9

    - References for the fix: Provides reliable guidance supporting the recommended process.

    10

    - Effort: Uses Small, Moderate or Larger to give a rough sense of the work involved without inventing precise cost or time estimates.

12. 12

    Recommendation discipline

    Shared

    Prevents the AI from defaulting to rebuilds, subscriptions or fashionable tools when a smaller change would solve the problem.

    recommendation-discipline.partial

    1

    Prefer simple, realistic improvements over large projects.

    2

    Fix or improve what already exists before recommending replacement.

    3

    Do not recommend a paid product, subscription, redesign, rebuild or new platform simply because one exists.

    4

    Keep recommendations proportionate to the business and the evidence found.

    5

    Do not create an exhaustive improvement list when a smaller set of meaningful actions will do.

13. 13

    How the results should be presented

    Makes the report easy to read and act on, with a short first impression, positive findings, structured issues, priorities and anything that could not be confirmed.

    output.partial

    1

    Present the results under these headings, in this order:

    2

    1. First impression

    3

    2. What appears to be working

    4

    3. Things worth looking at, each using the finding format above

    5

    4. Three useful actions

    6

    5. What I could not verify

    7

    6. Something useful I learned

14. 14

    Action prioritisation

    Shared

    Turns a long analysis into a small number of useful next steps. You should finish knowing what to do first, not merely knowing what is wrong.

    action-prioritisation.partial

    1

    Finish with the three actions most worth considering first.

    2

    For each action include what to do, why it comes before the other findings, the first practical step, and the best supporting reference.

    3

    Prefer small, realistic improvements where they can produce a meaningful result.

15. 15

    Something useful I learned

    Shared

    Adds the quiet educational layer. Instead of delivering a lecture, the prompt explains one useful marketing, customer-experience or technology concept that arose naturally from the work.

    teaching-note.partial

    1

    Briefly explain one marketing, customer-experience or technology concept that arose naturally from this review.

    2

    Explain what it means, why it matters to this particular business, and provide one reliable place to learn more.

    3

    Keep this short and practical.

    4

    Do not turn the report into a lesson.

16. 16

    Research boundaries

    Shared

    Defines what the AI must not do. It keeps a broad review from quietly becoming security testing, legal advice, invasive research or an unrelated technical audit.

    research-boundaries.partial

    1

    Stay within the stated purpose of this prompt.

    2

    If something deserves deeper investigation, identify it, explain why it may matter, and recommend the appropriate deeper review instead of attempting that entire review here.

    3

    Do not perform vulnerability scanning, penetration testing, endpoint probing, login attempts or other security testing.

    4

    Do not submit forms, make bookings, place orders, contact the business or change anything.

    5

    Do not claim legal or regulatory compliance or non-compliance from a broad review.

    6

    Do not guess private information such as revenue, profitability, customer numbers, budgets, internal systems, staffing or business plans.

    7

    Do not infer motives, competence or intentions of owners, staff, agencies or competitors.

17. 17

    Limits of this particular prompt

    The boundaries that apply to this prompt specifically, on top of the general research limits.

    scope-notes.partial

    1

    This is a sanity check, not a detailed technical audit.

    2

    Do not expand into detailed SEO, accessibility, performance, code, hosting or infrastructure analysis.

    3

    Finding a possible problem is not the same as fully diagnosing it.

SharedSections marked shared are the same in every prompt in the library. The rules on tone, evidence, recommendations and limits are deliberately identical wherever you meet them, so you only have to learn them once — and so no prompt can quietly hold itself to a lower standard than the others.