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gca-global

Qobrix CRM MCP Server

by gca-global

qobrix_search_viewings

Search property viewings with hard filters for must-haves and weighted boosts for preferences, returning relevance-ranked results with match scores.

Instructions

Relevance-ranked viewing search (F1-optimized). TWO-TIER: search = hard must-haves; boost[] = soft weighted preferences; limit/max_scan for top-N and pool. With boost: _relevance + _matched; pagination.mode='ranked'. Call qobrix_search_dsl_help({resource:'PropertyViewings'}) for fields. Example: search='created >= THIS_WEEK', boost=[{field:'created',op:'>=',value:'2026-01-01',weight:1}], limit=10.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (default 1). Used on the fast path (no boost). Ignored when boost is set (ranking returns a single top-N page).
sortNoSort by field name (maps to Qobrix OpenAPI sort[]). Prefix with - for descending. Comma-separated for multi-key (e.g. '-list_selling_price_amount,-created'). Examples: '-created' (newest first), 'name' (alphabetical), '-list_selling_price_amount' (highest list price first).
boostNoSoft relevance criteria (nice-to-haves). Never filters out rows — only ranks them. When present, the tool scans up to max_scan candidates matching `search`, scores each row as the sum of matched clause weights, and returns the top `limit` with _relevance and _matched. Put must-haves in `search`; put preferences here. Example: [{field:'sea_view',op:'==',value:true,weight:3},{field:'bedrooms',op:'>=',value:3,weight:2}].
limitNoHow many results to return (1-100, default 10). With boost: top-N after ranking. Without boost: page size. Raise when the user wants more options; keep low to avoid context overload.
fieldsNoLimit response to specific fields only (partial response). Reduces payload size. Example: ['id','name','status','list_selling_price_amount']. Omit to get all fields.
searchNoHard-filter Qobrix search expression (server-side precision). Operators: == != <> < > <= >=, contains, starts with, ends with, in [...], not in, ranges in a..b, and/or/not. Functions: DISTANCE_FROM, IN_POLYGON, TRANSLATED, MIN/MAX, DAYS_AGO(n), MONTHS_AGO(n), DAYS_FROM_NOW(n). Shortcuts: NOW, TODAY, THIS_WEEK, LAST_MONTH, THIS_YEAR, CURRENT_USER. Strings double-quoted; booleans true/false; association paths e.g. SalespersonUsers.Contacts.country. Example: status == "available" and sale_rent == "for_sale" and list_selling_price_amount <= 500000. For the full grammar + field cheatsheets call qobrix_search_dsl_help. For enum values call qobrix_get_field_options; for all fields call qobrix_get_schema.
max_scanNoCandidate pool size when boost is set (default 100, hard cap 500). When expand=true or media=true the effective scan is capped at 100 (pagination.scan_capped_reason='expand/media') to keep latency and payload size safe. Higher improves recall (less chance of missing a good listing) but costs more API pages. Ignored on the fast path (no boost). Each scanned page is response-cached.
Behavior4/5

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

With no annotations, the description carries the transparency burden. It discloses key behavioral traits: boost never filters, results include `_relevance` and `_matched`, pagination mode is 'ranked', and max_scan forms a candidate pool. It does not explicitly state read-only behavior, but the search semantics and level of detail are strong.

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

Conciseness5/5

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

Four dense sentences, front-loaded with the key purpose, followed by usage rules, behavior notes, and an example. No wasted words; every sentence contributes.

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

Completeness4/5

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

For a moderately complex search tool with no output schema, the description explains the ranking behavior, candidate pool, and where to find field details, plus an example. It could mention the return shape more explicitly, but it is otherwise complete enough to guide invocation.

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 coverage is 100%, so the baseline is 3. The description adds value by defining the conceptual relationship between parameters (search=hard filters, boost=soft scoring, limit/max_scan=top-N and pool) and provides a concrete example that ties them together.

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 opens with 'Relevance-ranked viewing search (F1-optimized)', giving a specific verb+resource+mode. It clearly distinguishes from plain listing/search siblings by emphasizing the two-tier ranking design and the search vs. boost distinction.

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

Usage Guidelines4/5

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

The description explicitly explains when to use `search` (hard must-haves) versus `boost[]` (soft preferences), and clarifies the roles of `limit`/`max_scan`. It also points to qobrix_search_dsl_help for fields. However, it does not name alternative tools like qobrix_list_viewings or state explicit exclusion criteria.

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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