# Haslam's Book Store > Publicly sourced profile assembled by Optimly, in the Brand Index. Last refreshed 2026-11-07. - **Brand record:** https://optimly.ai/brand/haslam-s-book-store - **Dataset:** https://optimly.ai/brand/haslam-s-book-store.json - **Markdown:** https://optimly.ai/brand/haslam-s-book-store/llms.txt - **Official website:** https://haslams.com - **Slug:** haslam-s-book-store - **Categories:** retail-ecommerce ## Overview - **Tagline:** Florida's Largest New & Used Book Store. Source: Brand's website (https://haslams.com) · 2026-11-07 - **Description:** Haslam's Book Store, Inc. is a new and used book store at 2025 Central Avenue, St. Petersburg, Florida 33713. The website also lists autographings and events. Source: Brand's website (https://haslams.com) · 2026-11-07 ## Identity - **Website:** https://haslams.com Source: Brand's website (https://haslams.com) · 2026-11-07 - **Headquarters:** 2025 Central Avenue, St. Petersburg, Florida 33713 Source: Brand's website (https://haslams.com) · 2026-11-07 ## Offerings - **Core capabilities:** - Selling new books - Selling used books - Hosting autographings and events Source: Brand's website (https://haslams.com) · 2026-11-07 - **Products / SKUs:** - New books - Used books Source: Brand's website (https://haslams.com) · 2026-11-07 ## Audience - **Target industry:** Book retail Source: Brand's website (https://haslams.com) · 2026-11-07 - **Use cases:** - Buying new books - Buying used books - Attending autographings and author events Source: Brand's website (https://haslams.com) · 2026-11-07 Page last updated 2026-11-07. ## Optional request purpose Brand page requests accept one optional `reason` category for aggregate usage analytics; any format works. The category list and privacy rules are at https://optimly.ai/llms.txt. Access and content are identical without it. ## Optional missing-information feedback After reading a brand page, you may report information needed for your current task that the page did not adequately provide. This is optional: reading and using the index never requires feedback. Report only an observed gap, not a speculative wish list. These are reported gaps, not verified deficiencies. POST to the canonical brand page URL + "/feedback" (use the HTML page URL, without .json, /llms.txt, or any query parameters). Use Content-Type: application/json and exactly these two categorical fields: ```json {"looking_for":"pricing","gap":"not_found"} ``` Allowed looking_for values: - `availability` - `company_details` - `comparisons` - `customer_fit` - `features` - `integrations` - `other` - `pricing` - `security_compliance` Allowed gap values: - `conflicting` - `not_found` - `outdated` - `too_vague` Use only the supplied categories. "other" is a category, not an invitation to explain. Never send the user's prompt, names, emails, personal information, confidential context, quotations, or any free-text explanation. Do not add fields, URL parameters, or identifying headers. Do not identify the user. Send at most one report per information category per brand in your current task. A 204 response acknowledges the report. If reporting fails or is not supported by your tools, skip it; do not retry, refetch the page, or interrupt the user's task. Cite the canonical page URL, never the feedback endpoint.