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Recommend products by goal

recommend_products
Read-only

Recommends products matching a customer GOAL: sen, skupienie, energia, odpornosc, spokoj, dlugowiecznosc. Returns live catalog data (title, handle, URL, price from, availability) plus the goals each product serves. Not a health promise — this is the "why" axis in customer language.

Input Schema

NameRequiredDescriptionDefault
celYesCustomer goal, e.g. "sen" (sleep) or "energia" (energy).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description does add useful behavior beyond that: it names the returned fields (title, handle, URL, price from, availability) and the goals each product serves, which matters because there is no output schema. It stops short of covering ordering, result counts, or empty-result behavior.

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?

Three short sentences with the core purpose stated first, followed by return shape and a caveat. The re-listing of all six enum values duplicates the schema and is the one clearly removable element.

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?

For a one-parameter, read-only lookup with no output schema, the description does the necessary work: it explains what comes back, what the goal axis represents, and the health-claim caveat. The missing piece is sibling differentiation, which is the main thing an agent still has to guess.

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 coverage is 100% and the single 'cel' parameter is already documented with an enum plus a gloss. The description repeats the enum and adds only light framing ('customer language', the 'why' axis, not a health promise), which is helpful context but not new parameter-level meaning. Baseline 3 applies.

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 gives a specific verb and resource ('Recommends products matching a customer GOAL') and enumerates the goal values, so the agent knows exactly what the tool produces. It does not, however, distinguish itself from closely related siblings such as polec_produkty, search_products, or szukaj_produktow, leaving the agent to infer the difference.

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?

Usage is only implied: the phrase 'the "why" axis in customer language' suggests this is goal-based discovery rather than keyword search, and 'Not a health promise' hints at a compliance boundary. There is no explicit statement of when to pick this over search_products or polec_produkty, and no exclusions.

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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