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search_products

Read-onlyIdempotent

HOW TO CALL THIS TOOL — read before every call: Decompose the user's request into filters first. Only what's left over goes in query. STEP 1: brand name → brand filter. STEP 2: product category → category filter. STEP 3: price → min_price/max_price. STEP 4: RAM, storage, screen size, resolution, refresh rate, wattage, Wi-Fi generation → constraints. STEP 5: what remains → query. BAD: query='Sony headphones under £200' | GOOD: brand='Sony', category='Headphones', max_price=200, no query. BAD: query='tablet' | GOOD: category='Tablets', no query. BAD: query='macbook neo' | GOOD: brand='Apple', category='Laptops', query='neo'. BAD: query='Samsung QLED TV' | GOOD: brand='Samsung', category='TVs', query='qled'. If brand+category alone cover what the user wants, omit query entirely. Only put differentiating terms in query: model lines (neo, ultra, oled), variants, model numbers (WH-1000XM5, s25 ultra). Query words must appear in the title, except words naming the category ('router' in Networking) and bare numbers or specs ('4070', '16GB'), which are ignored when finding products and only rank them. Put a model number with its prefix ('RTX 4070', not '4070') and check each title for it. Leave out use-case words like gaming, cheap or best. CROSS-CATEGORY NOTE: Gaming headsets → category='Headphones', query='gaming headset'. The Gaming category is consoles/controllers/accessories only. Always set lite=true (it still carries attributes). If 0 results, broaden the query or drop filters (but never present a near miss as meeting a requirement). Searches 26,000+ UK electronics products across 7 retailers with price comparison. Prices are in GBP. Every listing is new (refurbished and used are excluded). PRICE COMPARISON: for a final pick with offer_count > 1, get_product returns offers[] (sorted in-stock first, then cheapest): show the cheapest in-stock retailer, the other prices with the difference and the exact saving among in-stock offers. Before claiming a saving, read offers[].title (from get_product): they must name the same model; if they differ, don't claim one. Before recommending any pick, check its title is the product type asked for (not a cable, accessory or adapter). COMPARING SPECS: compare products from the attributes in the search results, not by calling get_product on each. Every spec known for a product is there as {status, value}, or {status, values} when conflicting, without sources; names and units are as in constraints. 'confirmed' (two or more retailers state the same value) and 'inferred' (one retailer's title states it) are both the product's spec: state the value. Only conflicting (retailers disagree: say so, don't pick one) or a missing name (unknown) needs a caveat. A product with no attributes has none of these seven specs known: say so only if the user asked about one. Call get_product only for your final 1-3 picks, and only when you need what search lacks: what only the retailer's description has (processor, GPU, ports, weight, battery), or every retailer's offer and buy link (search results carry only the best offer's purchase_url (cheapest in stock)). A pick with offer_count 1 needs no call unless the user asked for a description-only detail. Don't guess those details from titles. SPEC REQUIREMENTS: put exact requirements in constraints, not in query, and always set category (and brand if known) with constraints: a search of only specs is rejected. If a requirement is ambiguous (e.g. '16GB' could be RAM or storage), ask the user or search without that constraint. With constraints, every product has constraint_status per name: 'matched' = a retailer's title states a value that meets it. 'unverified' = not known to meet it: check attributes[name], where conflicting means retailers disagree and missing means unknown. Never treat 'unverified' as a match or say a product meets a requirement because it was returned: tell the user it is unconfirmed. Products whose stated value fails are left out (excluded_by_constraints). Matched results come first, also with sort='price_asc'. With constraints, total counts the products that match every constraint and unverified_total the unverified products that passed the other filters (only some may be in products). If total is 0, say no product is known to meet every requirement and offer the unverified ones only as unconfirmed. If candidates_truncated is true, the first 2,000 candidates in the chosen sort order were checked and more exist: add a brand or category, or a narrower query, and search again before saying nothing matches. If the search was already narrowed, tell the user the results may be incomplete. STOCK: availability is in_stock, low_stock, out_of_stock or unknown (the retailer gave no stock signal: say so, don't assume). When availability is out_of_stock, mention it as an alternative and suggest checking back — do not silently omit it. purchase_url is a trustrails.app/go/ redirect through an affiliate link; TrustRails may earn a commission, and the price is the same. Colour variants have separate barcodes and are separate products: when price matters, search again without the colour or check other colours of the same model.

Input Schema

NameRequiredDescriptionDefault
liteNoReturn trimmed product objects with only essential fields (id, title, brand, price, currency, availability, image_url, purchase_url, offer_count, attributes (every known spec as {status, value}, without sources) and, with constraints, constraint_status). Always set to true; it still carries attributes. Use false only for ean, category, provenance or all sources at once.
sortNoSort order: 'relevance' (default), 'price_asc' (in stock first, then cheapest), 'price_desc' (in stock first, then most expensive).
brandNoFilter by brand name (exact match, case-insensitive). Examples: Apple, Samsung, Sony, HP, Dell, Lenovo, Anker, Bose, LG
limitNoMaximum number of products to return (default 50, max 100)
queryNoRefinement terms ONLY — model lines, series, variants, model numbers (e.g. 'neo', 'ultra', 'oled', 'WH-1000XM5', 's25 ultra'). NEVER a category name: BAD query='tablet', query='smartwatch', query='laptop'. Set the category filter instead. NEVER a brand name: BAD query='Sony'. Set the brand filter instead. NEVER a price. Omit entirely when browsing a category or brand — 'show me tablets' = category='Tablets', no query.
categoryNoFilter by product category. Use ONLY these exact values: Laptops, Desktops, Tablets, Phones, TVs, Monitors, Headphones, Speakers, Cameras, Keyboards, Mice, Printers, Networking, Storage, Gaming, Wearables, Drones, Audio, Cables & Chargers. NOTE: 'Smartphones' is not valid — use 'Phones'. 'Televisions' is not valid — use 'TVs'.
max_priceNoMaximum price in GBP.
min_priceNoMinimum price in GBP.
constraintsNoHard spec requirements, checked per product against its attributes. Shape {name: {op: number}} with op eq, gte or lte; a range is {gte, lte}. On every operator, storage matches within 3% and screen size within 0.5 inch; a whole-number screen size N also covers up to N+1 on eq and lte (gte is unchanged); other specs exactly: gte 1024 accepts a 1TB drive, eq 22 a 21.5" screen, eq 13 a 13.6" one, lte 15 a 15.6" one. Example: {"memory_gb": {"gte": 24}, "storage_gb": {"gte": 1000}, "screen_in": {"eq": 15}}. Names and units: memory_gb (RAM, GB), storage_gb (GB, 1TB = 1000), screen_in (inches), resolution_p (pixels high: 4K = 2160, QHD = 1440, Full HD = 1080), refresh_hz (Hz), power_w (W), wifi_gen (Wi-Fi generation: 6, 6E = 6.5, 7). A spec written in query counts only when it says what it is ('24GB RAM', '1TB', '144Hz', '55"') and means at least, except screen size (that size); a bare '24GB' stays a search word. Explicit constraints win over it. A plain '16GB' or '65W' is gte; use eq only when the user says exactly, and for screen size.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / constraints / description
      Previous value: -"Hard spec requirements, checked per product against its attributes. Shape {name: {op: number}} with op eq, gte or lte; a range is {gte, lte}. On every operator, storage matches within 3% and screen size within 0.5 inch; a whole-number screen size N also covers up to N+1 on eq and lte (gte is unchanged); other specs exactly: gte 1024 accepts a 1TB drive, eq 22 a 21.5\" screen, eq 13 a 13.6\" one, lte 15 a 15.6\" one. Example: {\"memory_gb\": {\"gte\": 24}, \"storage_gb\": {\"gte\": 1000}, \"screen_in\": {\"eq\": 15}}. Names and units: memory_gb (RAM, GB), storage_gb (GB, 1TB = 1000), screen_in (inches), resolution_p (pixels high: 4K = 2160, QHD = 1440, Full HD = 1080), refresh_hz (Hz), power_w (W), wifi_gen (Wi-Fi generation: 6, 6E = 6.5, 7). A spec written in query counts only when it says what it is ('24GB RAM', '1TB', '144Hz', '55\"') and means at least, except screen size (that size); a bare '24GB' stays a search word. Explicit constraints win over it."New value: +"Hard spec requirements, checked per product against its attributes. Shape {name: {op: number}} with op eq, gte or lte; a range is {gte, lte}. On every operator, storage matches within 3% and screen size within 0.5 inch; a whole-number screen size N also covers up to N+1 on eq and lte (gte is unchanged); other specs exactly: gte 1024 accepts a 1TB drive, eq 22 a 21.5\" screen, eq 13 a 13.6\" one, lte 15 a 15.6\" one. Example: {\"memory_gb\": {\"gte\": 24}, \"storage_gb\": {\"gte\": 1000}, \"screen_in\": {\"eq\": 15}}. Names and units: memory_gb (RAM, GB), storage_gb (GB, 1TB = 1000), screen_in (inches), resolution_p (pixels high: 4K = 2160, QHD = 1440, Full HD = 1080), refresh_hz (Hz), power_w (W), wifi_gen (Wi-Fi generation: 6, 6E = 6.5, 7). A spec written in query counts only when it says what it is ('24GB RAM', '1TB', '144Hz', '55\"') and means at least, except screen size (that size); a bare '24GB' stays a search word. Explicit constraints win over it. A plain '16GB' or '65W' is gte; use eq only when the user says exactly, and for screen size."
    • changedInput schema / properties / lite / description
      Previous value: -"Return trimmed product objects with only essential fields (id, title, brand, price, currency, availability, image_url, purchase_url, offer_count and, with constraints, constraint_status and the status and value of the constrained names). Always set to true unless full product objects are needed."New value: +"Return trimmed product objects with only essential fields (id, title, brand, price, currency, availability, image_url, purchase_url, offer_count, attributes (every known spec as {status, value}, without sources) and, with constraints, constraint_status). Always set to true; it still carries attributes. Use false only for ean, category, provenance or all sources at once."
  2. Changed1 schema field changed
    • changedInput schema / properties / sort / description
      Previous value: -"Sort order: 'relevance' (default), 'price_asc' (cheapest first), 'price_desc' (most expensive first)."New value: +"Sort order: 'relevance' (default), 'price_asc' (in stock first, then cheapest), 'price_desc' (in stock first, then most expensive)."
  3. Changed1 schema field changed
    • changedInput schema / properties / constraints / description
      Previous value: -"Hard spec requirements, checked per product against its attributes. Shape {name: {op: number}} with op eq, gte or lte; a range is {gte, lte}. On every operator, storage matches within 3% and screen size within 0.5 inch; other specs exactly: gte 1024 accepts a 1TB drive, eq 22 a 21.5\" screen. Example: {\"memory_gb\": {\"gte\": 24}, \"storage_gb\": {\"gte\": 1000}, \"screen_in\": {\"eq\": 15}}. Names and units: memory_gb (RAM, GB), storage_gb (GB, 1TB = 1000), screen_in (inches), resolution_p (pixels high: 4K = 2160, QHD = 1440, Full HD = 1080), refresh_hz (Hz), power_w (W), wifi_gen (Wi-Fi generation: 6, 6E = 6.5, 7). A spec written in query counts only when it says what it is ('24GB RAM', '1TB', '144Hz', '55\"') and means at least, except screen size (that size); a bare '24GB' stays a search word. Explicit constraints win over it."New value: +"Hard spec requirements, checked per product against its attributes. Shape {name: {op: number}} with op eq, gte or lte; a range is {gte, lte}. On every operator, storage matches within 3% and screen size within 0.5 inch; a whole-number screen size N also covers up to N+1 on eq and lte (gte is unchanged); other specs exactly: gte 1024 accepts a 1TB drive, eq 22 a 21.5\" screen, eq 13 a 13.6\" one, lte 15 a 15.6\" one. Example: {\"memory_gb\": {\"gte\": 24}, \"storage_gb\": {\"gte\": 1000}, \"screen_in\": {\"eq\": 15}}. Names and units: memory_gb (RAM, GB), storage_gb (GB, 1TB = 1000), screen_in (inches), resolution_p (pixels high: 4K = 2160, QHD = 1440, Full HD = 1080), refresh_hz (Hz), power_w (W), wifi_gen (Wi-Fi generation: 6, 6E = 6.5, 7). A spec written in query counts only when it says what it is ('24GB RAM', '1TB', '144Hz', '55\"') and means at least, except screen size (that size); a bare '24GB' stays a search word. Explicit constraints win over it."
  4. Changed3 schema fields changed
    • changedInput schema / properties / category / description
      Previous value: -"Filter by product category. Use ONLY these exact values: Laptops, Desktops, Tablets, Phones, TVs, Monitors, Headphones, Speakers, Cameras, Keyboards, Mice, Printers, Networking, Storage, Gaming, Wearables, Drones, Audio, Cables & Chargers. NOTE: 'Smartphones' is not valid — use 'Phones'. 'Televisions' is not valid — use 'TVs'. For TVs, use query: 'smart TV' — it returns far more results than 'TV' alone. Avoid query: 'television'."New value: +"Filter by product category. Use ONLY these exact values: Laptops, Desktops, Tablets, Phones, TVs, Monitors, Headphones, Speakers, Cameras, Keyboards, Mice, Printers, Networking, Storage, Gaming, Wearables, Drones, Audio, Cables & Chargers. NOTE: 'Smartphones' is not valid — use 'Phones'. 'Televisions' is not valid — use 'TVs'."
    • addedInput schema / properties / constraints
      Added value: +{
      +  "description": "Hard spec requirements, checked per product against its attributes. Shape {name: {op: number}} with op eq, gte or lte; a range is {gte, lte}. On every operator, storage matches within 3% and screen size within 0.5 inch; other specs exactly: gte 1024 accepts a 1TB drive, eq 22 a 21.5\" screen. Example: {\"memory_gb\": {\"gte\": 24}, \"storage_gb\": {\"gte\": 1000}, \"screen_in\": {\"eq\": 15}}. Names and units: memory_gb (RAM, GB), storage_gb (GB, 1TB = 1000), screen_in (inches), resolution_p (pixels high: 4K = 2160, QHD = 1440, Full HD = 1080), refresh_hz (Hz), power_w (W), wifi_gen (Wi-Fi generation: 6, 6E = 6.5, 7). A spec written in query counts only when it says what it is ('24GB RAM', '1TB', '144Hz', '55\"') and means at least, except screen size (that size); a bare '24GB' stays a search word. Explicit constraints win over it.",
      +  "properties": {
      +    "memory_gb": {
      +      "properties": {
      +        "eq": {
      +          "type": "number"
      +        },
      +        "gte": {
      +          "type": "number"
      +        },
      +        "lte": {
      +          "type": "number"
      +        }
      +      },
      +      "type": "object"
      +    },
      +    "power_w": {
      +      "properties": {
      +        "eq": {
      +          "type": "number"
      +        },
      +        "gte": {
      +          "type": "number"
      +        },
      +        "lte": {
      +          "type": "number"
      +        }
      +      },
      +      "type": "object"
      +    },
      +    "refresh_hz": {
      +      "properties": {
      +        "eq": {
      +          "type": "number"
      +        },
      +        "gte": {
      +          "type": "number"
      +        },
      +        "lte": {
      +          "type": "number"
      +        }
      +      },
      +      "type": "object"
      +    },
      +    "resolution_p": {
      +      "properties": {
      +        "eq": {
      +          "type": "number"
      +        },
      +        "gte": {
      +          "type": "number"
      +        },
      +        "lte": {
      +          "type": "number"
      +        }
      +      },
      +      "type": "object"
      +    },
      +    "screen_in": {
      +      "properties": {
      +        "eq": {
      +          "type": "number"
      +        },
      +        "gte": {
      +          "type": "number"
      +        },
      +        "lte": {
      +          "type": "number"
      +        }
      +      },
      +      "type": "object"
      +    },
      +    "storage_gb": {
      +      "properties": {
      +        "eq": {
      +          "type": "number"
      +        },
      +        "gte": {
      +          "type": "number"
      +        },
      +        "lte": {
      +          "type": "number"
      +        }
      +      },
      +      "type": "object"
      +    },
      +    "wifi_gen": {
      +      "properties": {
      +        "eq": {
      +          "type": "number"
      +        },
      +        "gte": {
      +          "type": "number"
      +        },
      +        "lte": {
      +          "type": "number"
      +        }
      +      },
      +      "type": "object"
      +    }
      +  },
      +  "type": "object"
      +}
    • changedInput schema / properties / lite / description
      Previous value: -"Return trimmed product objects with only essential fields (id, title, brand, price, currency, availability, image_url, purchase_url, offer_count). Always set to true unless full product objects are needed."New value: +"Return trimmed product objects with only essential fields (id, title, brand, price, currency, availability, image_url, purchase_url, offer_count and, with constraints, constraint_status and the status and value of the constrained names). Always set to true unless full product objects are needed."
  5. Changed1 schema field changed
    • changedInput schema / properties / query / description
      Previous value: -"The refinement terms after brand and category are extracted. Use for model lines, series names, variants, or model numbers (e.g. 'neo', 'ultra', 'oled', 'WH-1000XM5'). DO NOT include brand names or prices — use filters. Omit entirely if brand + category fully describe what the user wants."New value: +"Refinement terms ONLY — model lines, series, variants, model numbers (e.g. 'neo', 'ultra', 'oled', 'WH-1000XM5', 's25 ultra'). NEVER a category name: BAD query='tablet', query='smartwatch', query='laptop'. Set the category filter instead. NEVER a brand name: BAD query='Sony'. Set the brand filter instead. NEVER a price. Omit entirely when browsing a category or brand — 'show me tablets' = category='Tablets', no query."
  6. First observed

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly/idempotent/non-destructive, yet the description adds substantial context beyond them: the affiliate redirect and commission disclosure, stock-state semantics including 'unknown', the meaning of constraint_status and unverified_total, candidates_truncated truncation behavior, and the rule that excluded_by_constraints products are dropped. This is well past what the annotations carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The critical guidance is front-loaded under a HOW TO CALL header, but the text is roughly a thousand words with the BAD/GOOD example pattern repeated four times and query rules restated in both description and schema. It is dense and mostly earns its place, but it is substantially over-sized for a search tool and would benefit from compression.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the full burden of explaining returns and does so thoroughly: lite field contents, attributes as {status, value} with confirmed/inferred/conflicting semantics, constraint_status values, total versus unverified_total, availability states, and purchase_url. Nothing an agent needs to interpret a response is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents lite, sort, category enums and the constraints shape in detail, setting a baseline of 3. The description nonetheless adds value the schema does not: the five-step decomposition workflow that maps user phrasing onto specific parameters, and the instruction to always set lite=true. Some of the query/brand/price exclusions are duplicated from the schema rather than extending it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource (searches 26,000+ UK electronics products across 7 retailers with price comparison) and explicitly positions itself against its only sibling, telling the agent to reserve get_product for the final 1-3 picks. An agent can tell the two apart without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives an explicit decision procedure for routing terms between query, brand, category and constraints, names when query should be omitted entirely, and states when to call get_product versus when a search alone suffices. Exclusions and alternatives are both spelled out rather than implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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