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Packrift Packaging

Explain no exact match

explain_no_exact_match
Read-onlyIdempotent

Explain why a nearby product should not be presented as an exact match for the buyer's spec, then return safe next actions and a quote-request URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
familyNoOptional product family.
reasonNoOptional short explanation from the caller.
requested_specYesThe buyer's exact requested packaging spec.
missing_or_mismatched_fieldsNoRequired fields that were unavailable or different, such as length, material, color, or pack_count.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the agent knows it is safe and side-effect-free. The description adds value by disclosing that it returns safe next actions and a quote-request URL, which is not captured in annotations. No contradictions.

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 a single, efficient sentence that states the purpose and expected outputs without wasted words. It is front-loaded with the primary action and includes a logical sequence ('then').

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?

For a tool with no output schema, the description clearly enumerates what is returned: an explanation, safe next actions, and a quote-request URL. Combined with the well-documented input schema, this provides sufficient context for an agent to invoke the tool correctly.

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 parameters are fully documented in the schema. The description adds minimal extra meaning beyond mapping 'buyer's spec' to requested_spec, but it does not explain family or reason usage. Baseline 3 is appropriate.

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 ('explain') and clearly identifies the resource (why a nearby product is not an exact match) and the outcome (safe next actions and a quote-request URL). This distinguishes it from sibling tools like compare_alternatives or get_pricing.

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 a clear usage context: when there is a nearby product that should not be presented as an exact match. It does not explicitly name alternatives or exclusions, but the context is unambiguous and the tool's niche is clear relative to siblings.

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

A3.9/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but there is potential confusion between inventory-checking tools (check_inventory vs. inventory_status) and cart-handoff tools (create_cart_url vs. prepare_purchase_handoff). Descriptions help differentiate, but an agent might occasionally select the wrong tool.

Naming Consistency4/5

The naming convention is generally consistent with verb_noun in snake_case (e.g., find_packaging_for_item, get_pricing). However, google_retail_ai_finder breaks the pattern with a company prefix, and some verbs vary (check vs. inventory_status). Overall clear and predictable.

Tool Count4/5

16 tools is slightly above the ideal 3-15 range, but still reasonable for a packaging e-commerce domain covering search, fit, inventory, pricing, shipping, and cart creation. Each tool serves a specific need, so the count feels appropriate.

Completeness4/5

The tool surface covers the core customer journey: product discovery, fit calculation, inventory/pricing checks, shipping estimation, cart handoff, reordering, and bulk quotes. Minor gaps exist (e.g., no order tracking or cancellation), but these are likely out of scope.

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