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US Brand Signal Rule Router

us-brand-signal-rule-router
Read-only

Turn normalized US brand signals and ordered rules into a deterministic routing plan with matched routes, unmatched IDs, counts, warnings, and reproducible digests. It never sends messages, calls destinations, fetches URLs, or infers identity. — $0.05/call, x402 (USDC on base).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYesfirstMatch uses the first matching rule; allMatches retains every matching rule in input order.firstMatch
rulesYesClosed explicit predicates. Runtime additionally enforces unique rule/route IDs, NFC and UTF-8 byte bounds, and confidenceMin <= confidenceMax because the Store schema dialect cannot compare sibling values.
signalsYesClosed rows. Runtime additionally enforces unique IDs, NFC, 256 UTF-8-byte text bounds, a 256 KiB envelope, strict calendar timestamps, and finite 9-decimal confidence values.
schemaVersionYesClosed input and output contract version.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, lowering the bar. The description adds valuable context: determinism ('deterministic routing plan', 'reproducible digests'), side-effect-free behavior ('never sends messages, calls destinations, fetches URLs'), and the closed-world constraint ('or infers identity'). It also discloses pricing, which is beyond 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?

The description is two sentences with the main action front-loaded. The first sentence packs the core purpose and outputs without waste; the second sentence adds essential side-effect exclusions and pricing. Every phrase earns its place, and the structure is efficient.

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 tool's moderate complexity (4 top-level parameters, two nested array types) and rich schema, the description is complete enough. It describes the high-level behavior and lists the key output components, which is important since there is no output schema. The exclusion of identity inference and side effects further clarifies boundaries. A full output structure description would push it to 5, but the current level is solid.

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%, so the baseline is 3. The description adds minimal parameter semantics beyond the schema: it refers to 'normalized US brand signals and ordered rules' as the inputs, but the schema already documents each property with detailed descriptions, enums, and constraints. The description does not need to compensate for missing schema info.

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's purpose: turning normalized US brand signals and ordered rules into a deterministic routing plan. It enumerates specific outputs (matched routes, unmatched IDs, counts, warnings, digests) and explicitly differentiates itself from sibling tools by noting it never sends messages, calls destinations, fetches URLs, or infers identity.

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 clear context for when to use this tool: when you need a deterministic routing plan from signals and rules. It also gives exclusions via 'never sends messages, calls destinations, fetches URLs, or infers identity,' implying alternatives are needed for messaging or identity inference. However, it does not explicitly name alternative tools or state 'use when...' versus 'do not use when...'.

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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TDQS

A3.8/5.0
Disambiguation2/5

Many tools have overlapping purposes, e.g., us-brand-signal-metrics-aggregator, us-brand-signal-cross-tabulator, and us-brand-signal-brand-summary all produce counts or summaries of the same type of data. The descriptions are detailed, but the boundaries between analyzers, summarizers, and aggregators are unclear enough that an agent may struggle to pick the right one.

Naming Consistency4/5

Most tools follow a consistent 'us-brand-' prefix with descriptive nouns separated by hyphens (e.g., us-brand-signal-batch-splitter, us-brand-evidence-chronology-builder). The exception is 'pricing_info', which uses an underscore and lacks the prefix, creating a minor inconsistency.

Tool Count3/5

At 21 tools, the set is on the heavier side but still manageable for a complex domain like brand intelligence. Many tools are variations on deterministic signal processing, which could be streamlined, but the count itself is not extreme.

Completeness3/5

The tool set covers a broad pipeline for processing buyer-supplied signals and evidence, including splitting, summarizing, routing, and building payloads. However, it lacks any tools for ingesting or fetching data from external sources (except one federal award snapshot), and there is no end-to-end controller that orchestrates the workflow. This leaves notable gaps for a complete 'brand intelligence' lifecycle.

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