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A2A Grocery — the agentic hub for retail grocery procurement

Search Cleared Items

search_cleared_items
Read-onlyIdempotent

Find items cleared for this market: validated SKU records in a market (query by product name, brand, maker or category; filters: temperature ambient · chilled · frozen · fresh, attribute lane organic · free-from · plant-based · artisan · origin · premium, department). Only validated rows are served; each item carries its claim status, market status and source class.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
laneNo
limitNo
queryNo
marketYes
departmentNo
decision_idNo
temperatureNo
product_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive), so the bar is lower, and the description adds a real constraint beyond them: 'Only validated rows are served,' plus that each item carries claim status, market status and source class. It stops short of 5 because pagination/limit behavior and the meaning of a 'validated' row are left implicit.

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?

Two sentences, front-loaded with the core verb and resource, and the filter enumeration is contained in a single parenthetical. The mid-dot filter list is dense but every element carries a distinct value, and there is no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return values need not be explained, and annotations carry the safety profile. But for an 8-parameter search tool with zero schema documentation, three parameters (limit, decision_id, product_type) remain undefined anywhere, leaving real gaps.

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 0% across 8 params, so the description must compensate. It clarifies query (product name, brand, maker, category), lane, temperature and department, and implies market, but leaves limit, decision_id and product_type entirely undocumented — a substantial portion of the surface.

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?

States a specific verb and resource: finds validated, market-cleared SKU records, and scopes the resource ('cleared for this market') in a way that separates it from generic lookups like get_item. It does not explicitly name a sibling to steer away from, so it stops just short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It conveys the searchable fields and available filters (temperature, lane, department), implying this is the search/browse entry point, but never says when to use this versus get_item, compare_items, or get_market_status, and gives no exclusions or prerequisites.

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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