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QQL syntax help

qql_help
Read-onlyIdempotent

Retrieve QQL reference sections by topic before writing queries to avoid rejections from unknown fields or invalid syntax.

Instructions

Read the QQL reference before writing a query. Pass a topic: overview, syntax, entities, operators, functions, examples, aggregation or enumValues. Field names differ per entity and from the write tools, and a query naming an unknown attribute is rejected — read entities first. Cost: no API call, about 2ms; cheaper than one rejected qql_search.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesWhich section to return (required — one section per call): - overview: what QQL is, overall query structure, subscription requirement - syntax: structure, ordering, custom fields, case-sensitivity, boolean and date fields - entities: the fields available on each entity — field names are NOT uniform across entities, so read this before writing a query against an unfamiliar one - operators: comparison, matching, set, null, and logical operators - functions: currentUser, activeUsers, and the now/startOf*/endOf* date functions - examples: ready-made queries for common questions - aggregation: SELECT (COUNT/MIN/MAX/AVG/SUM/FIRST/LAST), GROUP BY, HAVING — use this to count or summarise instead of paging through rows - enumValues: the valid values for priority, severity, and the per-entity status fields

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv3.0.0
    • removedInput schema / additionalProperties
      Removed value: -false
  2. Changed3 schema fields changedv2.1.1
    • changedInput schema / properties / topic / description
      Previous value: -"Specific help topic, or omit for general overview"New value: +"Which section to return (required — one section per call):\n- overview: what QQL is, overall query structure, subscription requirement\n- syntax: structure, ordering, custom fields, case-sensitivity, boolean and date fields\n- entities: the fields available on each entity — field names are NOT uniform across entities, so read this before writing a query against an unfamiliar one\n- operators: comparison, matching, set, null, and logical operators\n- functions: currentUser, activeUsers, and the now/startOf*/endOf* date functions\n- examples: ready-made queries for common questions\n- aggregation: SELECT (COUNT/MIN/MAX/AVG/SUM/FIRST/LAST), GROUP BY, HAVING — use this to count or summarise instead of paging through rows\n- enumValues: the valid values for priority, severity, and the per-entity status fields"
    • changedInput schema / properties / topic / enum
      Previous value: -[
-  "syntax",
-  "entities",
-  "operators",
-  "functions",
-  "examples"
-]New value: +[
+  "overview",
+  "syntax",
+  "entities",
+  "operators",
+  "functions",
+  "examples",
+  "aggregation",
+  "enumValues"
+]
    • addedInput schema / required
      Added value: +[
+  "topic"
+]
  3. First observedv1.1.7

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the bar is lower. The description adds real context the annotations do not: zero API-call cost, ~2ms latency, one section per call, and the failure mode where a query naming an unknown attribute is rejected.

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?

Front-loaded with the action and the parameter, then the topic list, then the cost/rationale. Every clause carries information, though the enum list is partially duplicated in the schema and could have been trimmed.

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 documentation-lookup tool with no output schema, the description covers what is returned (reference sections), call cost, and the sequencing rule for a first query. Only the exact return shape (text vs structured) is unspecified, which is minor.

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

Parameters3/5

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

Schema description coverage is 100% and the schema fully enumerates and explains all eight topic values, so the baseline is 3. The description restates the enum list but adds little syntax guidance beyond it, apart from the cross-entity field-name warning.

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?

Specific verb+resource: 'Read the QQL reference before writing a query', with the exact selector parameter named. It is clearly distinguishable from qql_search (which executes queries) and qase_tool_help (general tool help).

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?

Explicitly says when to use it: before writing a query, and specifically 'read `entities` first' when field names are unfamiliar. It also gives a concrete cost-based rationale ('cheaper than one rejected qql_search'), which is actionable routing guidance.

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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