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gca-global

Qobrix CRM MCP Server

by gca-global

qobrix_timeseries

Aggregate Qobrix CRM records into metrics (count, sum, avg, min, max) bucketed by day, week, month, quarter, or year, with date filters and optional prior-period comparison.

Instructions

Time-bucketed metric (count / sum / avg / min / max) over any resource. Paginates once over the window, buckets in-process by day/week/month/quarter/year (default 'month'). Per-resource default date_field: contracts→date_of_contract, opportunities/properties/calls/etc.→created. Use search to filter (e.g. only closed sales). Set compare_to_prior=true to also fetch the prior identical-length window for YoY %. Example uses: Monthly 2026 closed-sale volume with YoY: resource='contracts', metric='sum', field='final_selling_price_amount', year=2026, search='contract_type == "cos" and contract_status == "agreed"', compare_to_prior=true. Weekly lead intake last 90 days: resource='opportunities', bucket='week', metric='count', since_days=90. Quarterly listing additions 2026: resource='properties', bucket='quarter', year=2026, metric='count'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoISO date (YYYY-MM-DD) exclusive upper bound.
fromNoISO date (YYYY-MM-DD) inclusive lower bound.
yearNoCalendar year window.
fieldNoNumeric field aggregated by `metric` (required when metric != 'count'). Examples: 'final_selling_price_amount' (contracts), 'budget' (opportunities).
bucketNoBucket size (default 'month'). 'week' uses ISO weeks starting Monday.
metricNoAggregation inside each bucket (default 'count'). Anything other than 'count' requires `field`.
searchNoExtra raw Qobrix search expression ANDed with the date window.
resourceYesResource name (case-sensitive, lowercase plural as used by Qobrix API). Values: properties, opportunities, contacts, agents, tasks, property-viewings, projects, offers, contracts, calls, meetings, email-messages.
date_fieldNoDate column to bucket on. Defaults per-resource: contracts → date_of_contract, opportunities → created, properties → created, calls/meetings/email-messages/tasks → created.
since_daysNoRolling window: only rows dated within the last N days. Mutually exclusive with year/from/to.
compare_to_priorNoIf true, runs the same query over the prior identical-length window and returns a `prior` block + YoY % diffs (when buckets line up).
Behavior4/5

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

With no annotations, the description discloses important behavior: paginates once over the window, buckets in-process, per-resource default date_field, and prior-window behavior with YoY. It doesn't mention auth or rate limits, but covers the main operational traits.

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

Conciseness4/5

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

The description is front-loaded with the core purpose and then uses examples to illustrate parameter combinations. It is long but each sentence adds useful detail for an 11-parameter tool.

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?

Given the complexity and lack of annotations/output schema, the description covers defaults, windowing options, search filtering, and compare_to_prior. It doesn't fully specify the main return shape, but the examples and behavior notes make it reasonably complete.

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 covers all parameters, but the description adds value with per-resource date_field defaults, concrete search expressions, and example combinations. It clarifies semantics beyond the raw schema fields.

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

Purpose4/5

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

The description clearly states the tool computes time-bucketed metrics (count/sum/avg/min/max) over any resource, which is a specific verb+resource combination. It distinguishes from list/get siblings but does not explicitly differentiate from other analytics siblings like qobrix_aggregate.

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?

It gives concrete usage scenarios (e.g., monthly 2026 closed-sale volume with YoY, weekly lead intake) and explains when to use search and compare_to_prior. It does not state 'when not to use' or name alternatives, but the context is clear.

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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