{"server":"io.github.khan-ashifur/hooklayer","count":15,"changes":[{"tool":"product_scout","kind":"changed","observed_at":"2026-10-14T23:48:23.478Z","fields":["inputSchema","outputSchema"],"description_before":null,"description_after":null,"description_similarity":null,"before_hash":"6f8c6a69e63812378ac298d10e74d6f9","after_hash":"5bbbfa89c1275e544dbbf58fca7bbe8f"},{"tool":"product_scout","kind":"changed","observed_at":"2026-10-14T17:29:14.183Z","fields":["description","inputSchema","outputSchema"],"description_before":"Find and rank current TikTok Shop / social-commerce product opportunities using evidence rather than opinion. Use it to answer questions like 'what skincare products are breaking out in the US under $40', 'show me products with strong reviews but low competition', or 'what is worth testing in this niche right now'. Returns products ranked by a deterministic 9-component engine (demand, momentum, creator_adoption, competition, saturation, review_strength, price_attractiveness, creator_concentration, freshness), each carrying an opportunity status (emerging | promising | crowded | mature | cooling | insufficient_data), a confidence band, evidence-cited why_now[], risks[], insufficient_signals[] and history_coverage. The ranking is deterministic and contains no model output - read why_now, risks and components to explain to the user WHY something ranked where it did, and never present the score on its own. Provider-reported fields live under provider_reported.* and are null when TikTok did not expose them; null means unknown, never zero, and sold counts are never multiplied by price to imply revenue. There is no revenue or GMV field. To validate a single product in depth once you have a shortlist, call analyze_product - product_scout ranks a field of candidates, analyze_product interrogates one. Not for generic video search (use search_videos), creator analysis (use analyze_account), or any guaranteed-sales claim. Cost: 5 credits. Requires the shop_intelligence entitlement.","description_after":"Find and rank current TikTok Shop / social-commerce product opportunities using evidence rather than opinion. Use it to answer questions like 'what skincare products are breaking out in the US under $40', 'show me products with strong reviews but low competition', or 'what is worth testing in this niche right now'. Returns products ranked by a deterministic 9-component engine (demand, momentum, creator_adoption, competition, saturation, review_strength, price_attractiveness, creator_concentration, freshness), each carrying an opportunity status (emerging | promising | crowded | mature | cooling | insufficient_data), a qualification record (what passed, failed and is unknown), a confidence band, evidence-cited why_now[], risks[], insufficient_signals[] and history_coverage. Status comes from a qualification gate, never from the score: emerging needs measured sold-count growth across 3+ dated observations spanning 7+ days plus an independent signal (review growth or creator adoption over time); mature means established demand without verified growth; insufficient_data means trajectory cannot be verified yet, however high the score. verification_summary.outcome is NO_VERIFIED_OPPORTUNITIES whenever no returned product passed the gate - say so plainly instead of presenting the list as opportunities, and use verification_summary.by_status to explain whether the category or the filters were the limit. Amazon competition is never measured (AMAZON_COMPETITION_UNVERIFIED); never describe a product as unsaturated on Amazon. The ranking is deterministic and contains no model output - read qualification, why_now, risks and components to explain to the user WHY something ranked where it did, and never present the score on its own. Provider-reported fields live under provider_reported.* and are null when TikTok did not expose them; null means unknown, never zero, and sold counts are never multiplied by price to imply revenue. There is no revenue or GMV field. To validate a single product in depth once you have a shortlist, call analyze_product - product_scout ranks a field of candidates, analyze_product interrogates one. Not for generic video search (use search_videos), creator analysis (use analyze_account), or any guaranteed-sales claim. Cost: 5 credits. Requires the shop_intelligence entitlement.","description_similarity":0.748,"before_hash":"1b74d0c57bf188f6c8866cfd215552a8","after_hash":"6f8c6a69e63812378ac298d10e74d6f9"},{"tool":"search_videos","kind":"changed","observed_at":"2026-10-14T17:29:14.183Z","fields":["description","inputSchema","outputSchema"],"description_before":"Search for short-form videos by keyword across TikTok or Instagram. Returns up to 20 videos ranked by engagement, with view counts, likes, shares, comments, hashtags, author info, and URLs. Use when the user asks to find videos about a topic or keyword. Supports optional filters for niche, minimum views, recency window, and region.","description_after":"Search for short-form videos by keyword across TikTok or Instagram. Returns up to 20 videos ranked by engagement, with view counts, likes, shares, comments, hashtags, author info, and URLs. Use when the user asks to find videos about a topic or keyword. Supports optional filters for niche, minimum views, recency window, and region. Pass product_id to check which videos link a specific TikTok Shop product: linkage is exact_product_link only when the video carries that product link; keyword_match videos are NOT verified for that product, and evidence_summary.product_linkage.status is VIDEO_LINKAGE_UNVERIFIED when none link it. Region counts as verified only from the provider-reported video region; otherwise it is unknown. View counts are cumulative and do not show current acceleration.","description_similarity":0.561,"before_hash":"9b774a95bbc7c7dad70a5aff6db851cb","after_hash":"2eb6fba6a1dbb793674d02e801bb67d4"},{"tool":"product_scout","kind":"changed","observed_at":"2026-10-13T23:03:07.597Z","fields":["inputSchema"],"description_before":null,"description_after":null,"description_similarity":null,"before_hash":"dd7fafa69b5b8924399d176b3c709954","after_hash":"1b74d0c57bf188f6c8866cfd215552a8"},{"tool":"compare_saved_products","kind":"added","observed_at":"2026-10-09T00:11:56.618Z","fields":[],"description_before":null,"description_after":"Compare 2 to 4 saved analyze_product results side by side using only the stored evidence (identity, market proof, economics, competition, creator content, verdict). Read-only, 0 credits, no new analysis. Fields the source never reported are returned as not present, never estimated, and a freshness warning is included when the evidence ages differ by more than two days. Ids the user does not own come back in missing[]. Use after list_saved_research when the user asks which of their saved products to pursue.","description_similarity":null,"before_hash":null,"after_hash":"6db0ce9e722eacc986986b66b9aa49bf"},{"tool":"get_saved_research","kind":"added","observed_at":"2026-10-09T00:11:56.618Z","fields":[],"description_before":null,"description_after":"Retrieve one saved result in full (the stored research payload, what was asked, timestamps) by its saved_id. Read-only, 0 credits. Only the authenticated user's own results resolve; any other id is not found. Use when the user wants to reuse, re-read or build on something they saved earlier instead of paying to run the tool again.","description_similarity":null,"before_hash":null,"after_hash":"354a48c06cc6275fbfbc5f8ee89ee265"},{"tool":"list_saved_research","kind":"added","observed_at":"2026-10-09T00:11:56.618Z","fields":[],"description_before":null,"description_after":"List the authenticated user's saved HookLayer research (newest first by default). Read-only, 0 credits. Filter by kind, search titles, choose sort newest|oldest|title, include archived, and page with the returned cursor. Returns summaries (id, kind, title, timestamps, dashboard link), not the full result; call get_saved_research for one. Use when the user asks 'what have I saved', 'show my saved products', 'find the analysis I saved for @handle'.","description_similarity":null,"before_hash":null,"after_hash":"e7b3174e9bfe7916571ad3b0518f6929"},{"tool":"save_research","kind":"added","observed_at":"2026-10-09T00:11:56.618Z","fields":[],"description_before":null,"description_after":"Save a HookLayer result the user already received in this conversation so it appears under Saved Research in their HookMafia dashboard. 0 credits: this stores the result you already hold, it never re-runs the research tool. After a research result, offer once in one line to save it to HookMafia; call this only when the user says yes or asks to save, keep or bookmark a result. Pass the tool's structured result as `result` (billing and chain fields are dropped server-side), the kind that matches the tool, a short title, and a stable `request_id` so a retried save is deduplicated instead of duplicated. Returns the saved id and a dashboard link. Use list_saved_research / get_saved_research to read it back and compare_saved_products for 2-4 saved analyze_product results.","description_similarity":null,"before_hash":null,"after_hash":"d2b8f4aa927f6a4802980270ba300375"},{"tool":"brief_to_blueprint","kind":"changed","observed_at":"2026-10-04T17:01:25.412Z","fields":["inputSchema"],"description_before":null,"description_after":null,"description_similarity":null,"before_hash":"8ad004fc73bc6f3bd88794ea56cfdd14","after_hash":"fb527265a0dba08ad41ea9a438dcf21f"},{"tool":"find_viral_template","kind":"changed","observed_at":"2026-10-04T17:01:25.412Z","fields":["description","inputSchema"],"description_before":"Find proven viral templates in a niche with example videos. Returns templates ranked by performance, including hook patterns, format structures, average views, and example URLs. Use when the user asks what's working in a niche or wants concrete copyable structures. Supports 17 niches with optional angle narrowing via query parameter for more specific results (e.g., \"postpartum strength\" within Fitness).","description_after":"Find proven viral templates in a niche with example videos. Returns templates ranked by performance, including hook patterns, format structures, average views, and example URLs. Use when the user asks what's working in a niche or wants concrete copyable structures. Supports the 18 canonical niches with optional angle narrowing via query parameter for more specific results (e.g., \"postpartum strength\" within Fitness).","description_similarity":0.946,"before_hash":"a3f64e7a65da1c7279823b08fbdd01de","after_hash":"bbe5e859492fec087727262f9027d1d6"},{"tool":"trend_pulse","kind":"changed","observed_at":"2026-10-04T17:01:25.412Z","fields":["description","inputSchema"],"description_before":"Research what is currently gaining traction in short-form content for a specific niche. Returns rising opportunities (formats, hooks, styles, topics) with growth signals, data sources, and saturated patterns to avoid. Use when the user asks what to post about, what's trending in a niche, or needs to validate a content idea against current trends. Supports 17 niches and optional region filtering.","description_after":"Research what is currently gaining traction in short-form content for a specific niche. Returns rising opportunities (formats, hooks, styles, topics) with growth signals, data sources, and saturated patterns to avoid. Use when the user asks what to post about, what's trending in a niche, or needs to validate a content idea against current trends. Supports the 18 canonical niches and optional region filtering.","description_similarity":0.945,"before_hash":"5db7afc2726a84093ed9d6fed3d04a91","after_hash":"d19e629460147fb3f714bbd15c48d532"},{"tool":"analyze_account","kind":"changed","observed_at":"2026-10-04T17:01:25.412Z","fields":["outputSchema"],"description_before":null,"description_after":null,"description_similarity":null,"before_hash":"4b30f726e5ed9bc16c60a78d271947f8","after_hash":"9ca485226208385a01a99b31b450ad32"},{"tool":"analyze_product","kind":"added","observed_at":"2026-10-03T17:08:58.278Z","fields":[],"description_before":null,"description_after":"Deeply validate ONE TikTok Shop product before committing money or content to it. Give it a product_id from product_scout (or any TikTok Shop product URL) and it reads the listing, samples reviews across the full depth rather than only the most recent page, pulls comparable competitors, and returns what buyers actually say. You get: provider-reported sold / review / rating / price evidence; buyer voice split into what buyers praise and what they complain about; unmet needs and purchase objections in buyers' own words; return and fulfilment signal; a Why Now read; competitor intelligence and where rivals are weak; risks separated into product risks, market risks and data-confidence risks; and a 'how to beat this' synthesis of concrete differentiation angles traced back to specific review evidence. Every section states whether it resolved - provider facts, HookLayer analysis and genuinely unavailable evidence are distinguishable, and thin evidence is reported as thin rather than filled in. There is no revenue or GMV output and sold counts are never multiplied by price. Use product_scout first to find candidates, then this to decide between them. Cost: 10 credits. Requires the shop_intelligence entitlement.","description_similarity":null,"before_hash":null,"after_hash":"e080d92d2a432f4fe110ef9f91696e4b"},{"tool":"product_scout","kind":"added","observed_at":"2026-10-03T17:08:58.278Z","fields":[],"description_before":null,"description_after":"Find and rank current TikTok Shop / social-commerce product opportunities using evidence rather than opinion. Use it to answer questions like 'what skincare products are breaking out in the US under $40', 'show me products with strong reviews but low competition', or 'what is worth testing in this niche right now'. Returns products ranked by a deterministic 9-component engine (demand, momentum, creator_adoption, competition, saturation, review_strength, price_attractiveness, creator_concentration, freshness), each carrying an opportunity status (emerging | promising | crowded | mature | cooling | insufficient_data), a confidence band, evidence-cited why_now[], risks[], insufficient_signals[] and history_coverage. The ranking is deterministic and contains no model output - read why_now, risks and components to explain to the user WHY something ranked where it did, and never present the score on its own. Provider-reported fields live under provider_reported.* and are null when TikTok did not expose them; null means unknown, never zero, and sold counts are never multiplied by price to imply revenue. There is no revenue or GMV field. To validate a single product in depth once you have a shortlist, call analyze_product - product_scout ranks a field of candidates, analyze_product interrogates one. Not for generic video search (use search_videos), creator analysis (use analyze_account), or any guaranteed-sales claim. Cost: 5 credits. Requires the shop_intelligence entitlement.","description_similarity":null,"before_hash":null,"after_hash":"dd7fafa69b5b8924399d176b3c709954"},{"tool":"viral_remix","kind":"changed","observed_at":"2026-10-03T17:08:58.278Z","fields":["inputSchema"],"description_before":null,"description_after":null,"description_similarity":null,"before_hash":"25814ba0d0a3e238e72ae069b12e0591","after_hash":"d8001fa14a68783ab381b76a2cf2c06a"}],"next_before":null,"next_actions":[]}