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threadlinqs-cmd

Intel Threadlinqs MCP

Hunt Schema

hunt_schema
Read-onlyIdempotent

Learn the hunt query grammar: filterable fields, aliases, operators, stats-pipe forms, examples, and index freshness. Know the syntax to write valid hunting queries.

Instructions

The hunt query grammar: every filterable field and alias, which fields are scoped observables vs denormalized, the operators, the stats-pipe form, worked examples, and how fresh the index is. Call once before writing a hunt query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
grammarYes
row_countNo
rebuilt_atNo
duration_msNo
by_type_jsonNoJSON string of per-observation-type row counts.
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds substantive context: index freshness, coverage of the grammar, and a stable 'call once' nature. No contradiction exists between the description and annotations.

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?

Two tight sentences contain no filler. The content inventory is front-loaded and the usage instruction is direct.

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?

The description covers what the tool returns, when to call it, and how often. Combined with strong annotations and an output schema, an agent has everything needed to invoke it correctly.

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?

The tool takes zero parameters and schema coverage is complete, so the description does not need to explain parameters. The content description is relevant and sufficient for a no-argument schema reference.

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 identifies the tool as the authoritative source for the hunt query grammar, enumerating exactly what it contains: fields, aliases, operators, stats-pipe form, examples, and index freshness. This distinguishes it from the sibling hunt tool and other data-retrieval 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 phrase 'Call once before writing a hunt query' gives explicit when-to-use guidance and implies the result can be cached. It does not name alternatives or exclusions, but the tool is a targeted reference with no obvious alternative.

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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