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gca-global

Qobrix CRM MCP Server

by gca-global

qobrix_search_tasks

Search CRM tasks with hard filters and soft relevance boosts to rank results by priority. Ideal for daily pipeline and follow-up management.

Instructions

Relevance-ranked task search (F1-optimized) — daily ops for pipeline and follow-up. 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:'Tasks'}) for fields. Recipes: search='assigned_to == CURRENT_USER and status != "completed"', boost=[{field:'due_date',op:'<=',value:'2026-12-31',weight:3}], limit=15, max_scan=100. Overdue hard filter: due_date <= NOW and status == "pending".

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.
Behavior5/5

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

With no annotations provided, the description carries the full burden and excels: it discloses the two-tier semantics, that boost never filters but ranks, the `_relevance`/`_matched` return fields, pagination.mode='ranked', the fast-path vs boost behavior, and scan behavior including caps and response caching. This is far beyond minimal disclosure.

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?

The description is dense but well-structured, front-loaded with the core purpose and then systematically explaining the two-tier model, recipes, and edge cases. Every sentence contributes, with no filler or repetition of schema details.

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?

Given the tool's complexity (7 params, nested boost objects, no output schema), the description is remarkably complete: it covers the search grammar, boost behavior, pagination modes, return fields, and even provides ready-to-use recipes. It also points to qobrix_search_dsl_help for field-level details, making it self-sufficient for an agent.

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

Parameters5/5

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

Schema coverage is 100%, so baseline is 3, but the description adds substantial meaning: it explains how `search` and `boost` interact, when `page` is ignored, how `limit`/`max_scan` function as pool/top-N, and provides concrete recipes. This enriches the schema significantly.

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 uses a specific verb+resource ('Relevance-ranked task search') and clearly differentiates from siblings like qobrix_list_tasks by emphasizing the two-tier relevance ranking (search + boost). It also states the operational purpose ('daily ops for pipeline and follow-up'), giving it a distinct identity among similar search/list tools.

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 provides explicit usage guidance: hard must-haves go in `search`, soft preferences in `boost[]`, and explains `limit`/`max_scan` for top-N and pool. It includes recipes and directs users to qobrix_search_dsl_help for fields. However, it does not explicitly state when to prefer qobrix_list_tasks or other alternatives, so it stops short of full exclusions.

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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