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NocturnusAI

NocturnusAI

by Auctalis
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Hybrid

aggregate

Aggregate matching facts to compute COUNT, SUM, MIN, MAX, or AVG on a numeric argument at a specified position. Read-only operation with no side effects.

Instructions

Compute aggregations over matching facts. Supports COUNT, SUM, MIN, MAX, and AVG over a numeric argument at a specified position. Example: COUNT all score(player, ?) facts, or AVG scores at argIndex=1. Side effects: none (read-only). Auth: requires X-Tenant-ID header; FACT_READ permission when auth is enabled. Rate-limited per principal. Errors: VALIDATION_ERROR on unknown operation or missing argIndex for numeric ops.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "predicate": "<predicate>",
      "args": "<args>",
      "operation": "<operation>"
    },
    "name": "aggregate"
  }
}

Input Schema

NameRequiredDescriptionDefault
predicateYesThe predicate to aggregate over
argsYesPattern arguments — use ?x as wildcards, concrete values to constrain
operationYesAggregation operation: COUNT, SUM, MIN, MAX, or AVG
argIndexNo0-based argument position to aggregate for SUM/MIN/MAX/AVG (ignored for COUNT)
scopeNoOptional scope filter

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.12

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description fully discloses behavioral traits: read-only (no side effects), auth needs, rate limiting, and error conditions (VALIDATION_ERROR). No contradictions.

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 concise (three sentences), front-loaded with purpose, and includes key details (operations, example, side effects, auth, errors) without redundancy.

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 of aggregation with multiple operations and argIndex, the description covers essential aspects. It lacks explicit output format, but the example implies a numeric result, which is sufficient.

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%, and the description adds meaning beyond the schema: explains operation and argIndex interaction, gives an example. The example clarifies usage, providing extra context.

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 clearly states the tool computes aggregations over facts, lists supported operations (COUNT, SUM, MIN, MAX, AVG), and gives an example. It is a specific verb+resource with no sibling ambiguity.

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 context on when to use (read-only aggregation), auth requirements (X-Tenant-ID, FACT_READ permission), rate limits, and error types. It lacks explicit when-not-to-use or alternatives, but no sibling tool overlaps.

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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