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frothkoetter

data-marketplace-mcp-server

by frothkoetter

submit_product_feedback

Submit a 1–5 star rating with an optional comment to share data quality feedback for a specific product, helping providers identify and address quality issues.

Instructions

Sterne-Feedback zur Datenqualität abgeben (1–5).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
userYes
ratingYes
commentNo
product_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It reveals the tool submits feedback (a write/mutation action), but doesn't disclose whether feedback is editable, whether duplicates are allowed, whether submission affects product ratings, or what the response/return format is. For a mutation tool with zero annotation coverage, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely short (one sentence fragment). While brevity is generally positive, this borders on under-specification rather than conciseness. A tool description should be concise but still informative; this one is efficient but delivers nearly no value beyond the tool name itself.

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

Completeness1/5

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

The description is completely inadequate for a tool with 4 parameters (3 required) and a write operation. It provides no usage guidance, no parameter semantics, no behavioral transparency, and no output expectations. While an output schema exists (which covers return value documentation), the description fails to cover purpose nuance, preconditions, or effect of the action. This is a minimal viable description at best.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate, but it provides essentially no parameter information. The description mentions ratings 1-5, which maps to the 'rating' parameter's valid range, adding minimal value there. However, there are three required parameters (product_id, user, rating) plus an optional comment, none of which are explained in terms of format, validation, or semantics beyond raw schema types.

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

Purpose2/5

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

The description 'Sterne-Feedback zur Datenqualität abgeben (1–5)' (submit star feedback on data quality 1-5) states a verb and resource, but it's minimal and doesn't distinguish this from any feedback tool. It does indicate it's about data quality rating, which adds some specificity, but it doesn't describe what happens with the feedback or differentiate it clearly from siblings. The description is essentially a single fragment without contextual detail.

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

Usage Guidelines1/5

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

No guidance is provided on when to use this tool versus alternatives. The description doesn't explain context, prerequisites, or when this tool should be preferred over any of the 15 sibling tools. There is no mention of when to use it, what conditions apply, or how it relates to other feedback or marketplace tools.

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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