US Brand Intelligence

US Brand Evidence Snapshot Diff

us-brand-evidence-snapshot-diff

Read-only

Compare two small buyer-supplied US brand evidence snapshots and return a stable machine-readable report of added, removed, changed, and unchanged records. Inline-only, deterministic, and designed for agents that already own both snapshots. — $0.05/call, x402 (USDC on base).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`primary`	Yes	One to 50 rows for the side selected by primarySide. Identical rows are rejected structurally; runtime also rejects the same dedupeKey across non-identical rows.
`counterpart`	No	Optional one to 50 rows for the opposite side; omit it for an empty counterpart snapshot. Runtime rejects repeated dedupeKey values.
`primarySide`	Yes	Whether primary rows are the before or after snapshot.	before
`schemaVersion`	Yes	schemaVersion	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, openWorldHint=true, and destructiveHint=false, covering the safety profile. The description adds valuable behavioral context: 'Inline-only, deterministic,' 'stable machine-readable report,' and the explicit operation of comparing two snapshots, which goes beyond what annotations alone convey.

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 no filler. It front-loads the core action and result, then adds relevant constraints and pricing. Every clause earns its place, making it efficient and clear.

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 rich input schema and annotations, the description is largely complete. It explains purpose, use context, determinism, and inline-only behavior. It does not specify the exact output format, but the stated report categories and the presence of no output schema keep this from being a major gap.

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 schema already documents all four parameters, including nested fields. The description adds high-level context like 'buyer-supplied' and 'both snapshots,' but does not improve per-parameter semantics beyond what the schema provides, warranting the baseline score.

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 uses a specific verb ('Compare') with a clear resource ('two small buyer-supplied US brand evidence snapshots') and specifies the output categories ('added, removed, changed, and unchanged records'). This clearly distinguishes it from sibling tools like chronology builders or normalizers.

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 states it is 'designed for agents that already own both snapshots,' giving clear context for when to use it. It also notes 'Inline-only,' which implies when external fetching is not appropriate, though it does not explicitly name alternative tools.

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.

Resources

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