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commerce-evidence-toolkit

compare_feed_snapshots

Read-onlyIdempotent

Compare source and feed snapshots to identify discrepancies in item IDs, USD prices, sale state, and availability. Returns hold decision when evidence is unresolved, without fetching or writing feeds.

Instructions

Compare supplied source and feed snapshots for exact item IDs, current USD prices, sale state and availability. Requires schemaVersion 1.0, profile openai-native-stable, explicit asOf, maxAgeHours, capturedAt and evidenceRef. Unresolved evidence yields hold with no proposed changes. No fetches or feed writes. See examples/feed-snapshots.json.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe, non-destructive operation. The description adds context by stating 'No fetches or feed writes', which reinforces the read-only nature and explicitly indicates no side effects. It also mentions the behavioral outcome of unresolved evidence (hold with no proposed changes), which is beyond the annotations. The bar is lowered due to annotations, and the description adds meaningful context.

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?

The description is concise, with three sentences that pack essential information: what it does, required parameters, and outcome. It front-loads the core purpose and then adds constraints and side-effect disclosures. The reference to an example file is a minor addition but not wasteful. It could be considered slightly dense but well-structured for an agent to parse quickly.

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 (single parameter that is a complex object with nested structures), the description covers the essential aspects: inputs, required fields, behavior on unresolved evidence, and side effects. The output schema is absent, but the description doesn't need to explain return values if the agent can infer expected changes from the context. The description is sufficient for an agent to call the tool correctly, though it could benefit from mentioning the exact format of the asOf timestamp or maxAgeHours constraints, but that's not critical.

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?

The schema has zero description coverage for parameters, so the description carries the burden of explaining parameter meaning. The description mentions several required parameters (schemaVersion, profile, asOf, maxAgeHours, capturedAt, evidenceRef) and clarifies that they are explicit requirements, but it does not provide definitions or formats for each parameter beyond their names. For nested objects like 'feed' and 'source', the schema already defines their structure, and the description implies they contain items with price, item_id, etc. The description adds minimal value over the schema since it only lists parameter names, not their semantic meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: comparing source and feed snapshots for specific attributes (item IDs, USD prices, sale state, availability). It specifies the action (compare) and the resource (snapshots), which helps distinguish it from siblings like 'compare_dimensions' which likely compares dimensions, not prices. However, it does not explicitly name the siblings or contrast with them directly in the description, so it misses full differentiation.

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 implies when to use this tool by specifying the data it compares (exact item IDs, prices, sale state, availability) and the required parameters (schemaVersion, profile, asOf, maxAgeHours, capturedAt, evidenceRef). It also states the consequence of unresolved evidence (hold with no changes), which guides the agent on expected outcomes. However, it does not explicitly say when not to use it or suggest alternatives, so it lacks explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.