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Documentation Index

Fetch the complete documentation index at: https://docs.mangrovesystems.com/llms.txt

Use this file to discover all available pages before exploring further.

Rule expressions are written in a small expression language with familiar comparison and logical operators. Each expression is a condition — when it evaluates to true on a record, that record is flagged with an alert. 
{{carbon_content}} not between 0.50 and 0.90
This page is the reference for the full set of operators and patterns. For a walkthrough of writing your first rule, see Create a Data Rule.

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Variables

Variables reference the data Mangrove evaluates the expression against. They are wrapped in double curly braces. 
{{slug}}
The values the rule editor offers depend on the rule’s target:
  • Event Data rules — variables are datapoint slugs from your project’s data point types. Selecting a specific event type scopes the rule to that event type and narrows autocomplete to its datapoints — we recommend doing this so the rule’s intent is clear. If no event type is selected, the rule evaluates against any event in the project whose datapoints satisfy the expression.
  • Batch Calculations rules — variables are nodes in the selected model. When multiple nodes share the same slug, qualify the reference with the datapoint type using the form node."<NodeName>".<slug> (for example, node."Mass".biochar_mass).
Type {{ in the rule editor to open autocomplete. Each suggestion shows the variable name and its description, value type, or unit when available.

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Comparison operators

OperatorMeaning
=Equal to
!=Not equal to
<Less than
<=Less than or equal to
>Greater than
>=Greater than or equal to
{{ash_content}} > 0.05
{{batch_status}} != 'verified'

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Logical operators

Combine conditions with AND, OR, and NOT. Use parentheses to group. 
{{ash_content}} > 0.05 AND {{moisture}} < 0.10
NOT ({{feedstock_type}} = 'manure' OR {{feedstock_type}} = 'crop_residue')

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Range and set operators

OperatorExampleTriggers when…
BETWEEN ... AND ...{{ph}} between 6.0 and 8.0The value is within the range (inclusive).
NOT BETWEEN ... AND ...{{ph}} not between 6.0 and 8.0The value is outside the range.
IN (...){{country}} in ('US', 'CA', 'MX')The value matches any item in the list.
NOT IN (...){{country}} not in ('US', 'CA')The value matches none of the items in the list.

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Text operators

OperatorExampleTriggers when…
CONTAINS{{notes}} contains 'override'The text contains the substring.
STARTS WITH{{tracking_id}} starts with 'TMP-'The text starts with the prefix.
ENDS WITH{{filename}} ends with '.csv'The text ends with the suffix.
MATCHES{{lot_code}} matches '[A-Z]{2}-[0-9]+'The text matches the regular expression.
String literals use single quotes.

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Presence operators

Use these to check whether a value was recorded at all.
OperatorTriggers when…
IS MISSINGThe variable has no value.
IS PRESENTThe variable has any value.
The variable must be one of your project’s datapoint slugs (or a model node, for Batch Calculations rules): 
{{lab_sample_id}} is missing
{{adjustment_note}} is present AND {{adjustment_note}} = 'manual'

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Aggregates

Aggregate functions roll a set of values into a single number. They are most useful in Batch Calculations rules, where a model node may hold many values across a batch.
FunctionReturns
COUNTNumber of values
SUMSum of values
AVGAverage of values
MINSmallest value
MAXLargest value
SUM({{batch_input_mass}}) > 1000
AVG({{moisture}}) not between 0.05 and 0.15
COUNT({{lab_sample}}) < 3

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Booleans and numbers

  • Booleans are written true and false (case-insensitive).
  • Numbers are written without quotes — both integers and decimals work: 0, 42, 3.14, 0.005.

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Common patterns

These examples assume your project has datapoints with the slugs shown — substitute slugs that exist in your project. 
# Out-of-range alert
{{carbon_content}} not between 0.50 and 0.90

# Missing required value
{{lab_sample_id}} is missing

# Tracking ID format check
{{tracking_id}} not matches '[A-Z]{2}-[0-9]{6}'

# Batch CI sanity check
{{ci_score}} > 30 OR {{ci_score}} < -50

# Insufficient lab samples in a batch
COUNT({{lab_sample_id}}) < 3

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Tips for writing good rules

  • Phrase the rule as the failure case. A rule with the expression {{ph}} not between 6.0 and 8.0 triggers when pH is out of range — that’s the alert you want.
  • Start specific. Scope to an event type when possible. Broad rules across all event types are harder to interpret when they fire.
  • Validate before saving. The validate step previews matches against recent data — use it to catch over-eager rules before they generate noise.
  • Prefer presence checks over equality with empty string. Use IS MISSING rather than = '' to detect missing values.
  • Use comments in the rule name. Since expressions are terse, lean on the rule name and description to explain why the rule exists.