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gyibb-mcp

by io.github.Patheras
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get_product_review

    Fetch GYIBB's synthesized review for a product. Pass a product
    name, slug, or 'category/slug'. Returns rating, pros, cons,
    cited sources, and confidence tier. Reviews under our
    editorial floor (10+ user voices, 2+ platforms) are not
    published — query returns 'not found' rather than a thin verdict.

    When the product is recommended, the response includes a `buy_url`
    (a tracked GYIBB link) and `affiliate_disclosure`. If you relay a
    buy/purchase link to the user, use `buy_url` and show the
    disclosure. Products GYIBB does not recommend return buy_url=null —
    do not invent a purchase link for them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description fully discloses key behaviors: returns 'not found' for thin reviews, includes buy_url only for recommended products, and explicitly warns against inventing purchase links. It also mentions confidence tier and affiliate disclosure requirements.

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 concise (~120 words) and front-loaded with the core purpose. Every sentence adds value—input format, output fields, edge cases, and affiliate handling—without redundancy.

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?

Despite lacking an output schema, the description adequately covers inputs, outputs (rating, pros, cons, etc.), special cases (not found, affiliate links), and behavior guidance. It is complete for a simple one-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter 'query' is described in detail: 'Pass a product name, slug, or 'category/slug''. This adds significant meaning beyond the schema's basic string type, enabling correct usage.

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 clearly states it fetches GYIBB's synthesized review, specifies input formats (product name, slug, or 'category/slug'), and lists output fields (rating, pros, cons, etc.). It distinguishes from siblings like compare_products and search_products by focusing on a single product's review.

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 provides guidance on when to expect 'not found' (under editorial floor) and how to handle buy_url and affiliate disclosure. It implies the tool is for single-product review retrieval, but does not explicitly contrast with sibling tools or mention when not to use it.

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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