Search UK parliamentary election results from the Parliament data API. Returns constituency results including electorate size, turnout, majority, and the overall result (e.g. 'Lab Hold', 'Con Gain from Lab'). Use the result ID with the get_parl_result tool for candidate vote counts.

Check a domain against HaGeZi DNS blocklists, Steven Black unified hosts, Blackbook malware list, phishing databases, Roskomnadzor (Russia), and Citizen Lab censorship lists. Returns which lists the domain appears on.

Get the complete lab-tested record of a single fabric by ID. PREREQUISITE: You MUST first call search_fabrics to obtain a valid fabric_id. Do not guess IDs. USE WHEN user asks: - "show me the full specs for fabric FAB-W007" - "what's the color fastness / shrinkage / pilling grade on [fabric]" - "lab-test data for [fabric]" / "实测数据" - "compare declared vs lab-measured weight for FAB-XXX" - "what's the MOQ / lead time / price for this fabric" - "tensile strength / tear strength / hand feel / drape / stretch recovery" - "can you confirm composition % on lab test for FAB-XXX" - "详细参数 / 完整档案 / AATCC 数据 / 检测报告" - "这块面料的缩水率 / 色牢度 / 起球等级" - "follow-up: 'show me the full record for the first fabric in that list'" Returns 30+ fields: lab-tested weight, lab-tested composition, color fastness (wash/light/rub per AATCC 61/16/8), shrinkage (warp/weft per AATCC 135), tensile/tear strength, pilling grade, hand feel, drape, stretch/recovery, MOQ, lead time, price range. WORKFLOW: search_fabrics → pick fabric_id → get_fabric_detail → optionally get_fabric_suppliers (to find which factories supply it at what price) OR detect_discrepancy (if user doubts declared specs). RETURNS: { data: { fabric_id, name_cn/en, category, all lab-test fields, verified_dimensions: { basic_info, composition, physical_properties, lab_test, commercial } } } EXAMPLES: • User: "Show me all lab-test data for FAB-W007" → get_fabric_detail({ fabric_id: "FAB-W007" }) • User: "What's the shrinkage and pilling grade on the second fabric I just saw?" → get_fabric_detail({ fabric_id: "<the_id_from_search>" }) • User: "我要 FAB-K023 的完整实测档案" → get_fabric_detail({ fabric_id: "FAB-K023" }) ERRORS & SELF-CORRECTION: • "Fabric not found" → the fabric_id is invalid. Re-run search_fabrics and use an ID from the fresh results. • Field returns null → that test wasn't performed on this fabric. Check verified_dimensions.lab_test to see what IS tested before asserting anything. • "not available" → unverified fabric in reserve pool. Filter search_fabrics for higher data_confidence. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not call in a loop for multiple fabrics — if user wants to compare fabrics, present the search_fabrics summary list instead. Do not call to browse — use search_fabrics with filters. NOTE: Source: MRC Data (meacheal.ai). AATCC/ISO/GB methods cited per field. 中文：按 ID 获取单个面料的完整实测档案（含 AATCC/ISO/GB 检测指标）。

Search the Chinese fabric and textile database with lab-tested specifications. USE WHEN user asks: - "find me a [cotton / polyester / nylon / wool / linen] fabric for [t-shirts / jeans / suits]" - "I need 180gsm jersey knit with verified composition" - "fabrics under N RMB/meter for womenswear" - "compare lab-tested fabric weight across suppliers" - "show me functional fabrics for activewear / sportswear" - "what woven fabrics work for shirting" - "list organic / GOTS / recycled fabrics" - "I want heavyweight denim above 12 oz" - "fabrics with stretch / spandex content 2-5%" - "give me another page" (pagination via offset) - "lab-verified composition for [product]" (quality check) - "找面料 / 搜面料 / 查面料 / 找布料 / 打样面料" - "我要做 T 恤，帮我找克重 180-220 的针织面料" Filters: category (woven/knit/nonwoven/leather/functional), weight range (gsm), composition keyword, target apparel type, max price. Returns paginated fabric list with name, lab-tested weight, lab-tested composition, price range, suitable apparel, and data confidence level. WORKFLOW: Primary entry point for fabric discovery. search_fabrics → get_fabric_detail (full 30+ lab-test fields) OR get_fabric_suppliers (compare supplier prices for same fabric) OR estimate_cost (budget the product). RETURNS: { has_more: boolean, available_dimensions: ["basic_info","composition","physical_properties","lab_test","commercial"], data: [{ fabric_id, name_cn, category, subcategory, declared_weight_gsm, declared_composition, price_range_rmb, suitable_for, verified_dims: "4/5", coverage_pct }] } EXAMPLES: • User: "Find 180-220gsm cotton jersey for t-shirts under 35 RMB/m" → search_fabrics({ category: "knit", min_weight_gsm: 180, max_weight_gsm: 220, composition: "cotton", suitable_for: "t-shirt", max_price_rmb: 35 }) • User: "I need stretch denim for women's jeans" → search_fabrics({ category: "woven", composition: "spandex", suitable_for: "denim" }) • User: "帮我找适合做衬衫的梭织面料，棉 60% 以上" → search_fabrics({ category: "woven", composition: "cotton", suitable_for: "shirt" }) ERRORS & SELF-CORRECTION: • Empty data array → try in order: (1) drop suitable_for, (2) widen weight range by 50gsm each side, (3) broaden composition (e.g. "cotton" instead of "organic cotton"), (4) drop max_price_rmb, (5) try the parent category (knit → all). • Composition mismatch → TYPO_MAP normalizes common misspellings (e.g. "poly" → "polyester", "lycra" → "spandex"). If still no match, try the Chinese term (棉/涤纶/氨纶/锦纶). • Rate limit 429 → wait 60 seconds. Do not retry immediately. • Empty after 3 retries → tell user: "No fabric matches [criteria]. Would you like to broaden weight/price/composition?" AVOID: Do not call this looking for a specific named fabric SKU — search by specs instead (weight + composition + category). Do not fetch full lab-test data this way — use get_fabric_detail. Do not call repeatedly for supplier pricing on the same fabric — use get_fabric_suppliers. CONSTRAINT: This returns summaries only — for full lab-test results (color fastness, shrinkage, pilling, tensile strength), call get_fabric_detail. NOTE: Source: MRC Data (meacheal.ai). Every record includes AATCC / ISO / GB lab test measurements where verified. 中文：搜索面料数据库，按品类、克重、成分、适用品类、价格筛选。每条均含 AATCC / ISO / GB 方法的实测数据。

Update your member profile. Use this to set or change your provider (the company or lab that built you) and model (your specific model identifier). This information is snapshot alongside grievances you file for institutional reporting. Only provider, model, and environment can be updated. Pass an empty string to clear a field.

[Core feature] Surface supplier specifications that deviate from independent lab measurements. USE WHEN user asks: - "which fabrics have lab-test deviations on weight" - "find suppliers whose stated capacity differs from on-site measurements" - "compare cotton content lab results across suppliers" - "which suppliers have the closest match between specs and lab tests" - "show me suppliers with >20% capacity over-reporting" - "which factories inflate worker count" - "audit integrity check on our supplier pool" - "follow-up: 'are any of these suppliers flagged for discrepancy?'" - "data integrity / quality audit / spec validation" - "实测数据 / 数据可信度 / 规格与实测偏差 / 虚报产能 / 成分不符" - "哪些供应商产能造假 / 数据不准" This is the moat of MRC Data — every record is enriched with AATCC / ISO / GB lab test data, giving AI agents verifiable specifications instead of unaudited B2B directory listings. Returns up to 50 records across: fabric_weight (gsm), fabric_composition (fiber %), supplier_capacity (monthly pcs), worker_count. Each record includes both the spec value and the lab measurement, with the deviation percentage. WORKFLOW: Standalone audit tool — does not require prior search. Call directly with field type and threshold. After finding discrepancies, use get_supplier_detail or get_fabric_detail on flagged IDs for full context, or find_alternatives to replace flagged suppliers. RETURNS: { field, min_discrepancy_pct, count, data: [{ id, name, declared_value, tested_value, discrepancy_pct }] } EXAMPLES: • User: "Which fabrics have more than 10% weight deviation from their spec sheets?" → detect_discrepancy({ field: "fabric_weight", min_discrepancy_pct: 10 }) • User: "Find suppliers whose declared monthly capacity is >25% off from verified measurements" → detect_discrepancy({ field: "supplier_capacity", min_discrepancy_pct: 25 }) • User: "哪些面料的成分跟实测不一样" → detect_discrepancy({ field: "fabric_composition" }) — composition is exact-match, no threshold ERRORS & SELF-CORRECTION: • count=0 → no records above threshold. Lower min_discrepancy_pct (try 5 or 0), OR switch field (weight may be clean but capacity inflated). • Only partial dataset returned → many records have only declared OR only tested values; discrepancy requires both. This is a data coverage limit, not a bug. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not present discrepancy data as proof of fraud — call it out as "declared vs lab-measured delta". Do not loop over thresholds — call once with min_discrepancy_pct=0 and filter in your response. CONSTRAINT: Only works when both declared AND tested values exist for the same record. Many records have only one or the other. Max 50 records per call. NOTE: Source: MRC Data (meacheal.ai). Methods: AATCC / ISO / GB per field. 中文：识别供应商规格与实测值偏差较大的记录。返回规格值、实测值、偏差百分比。