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ListingGood MCP

by io.github.ryanyang828

compliance_scan

Deep knowledge-base compliance audit (async; 2 credits).

Produces a thorough, written risk report covering prohibited words, IP, category
mismatches, GPSR and more, backed by a private 15-year compliance knowledge base.

Use this when you need a complete, actionable compliance report. Do NOT use it for a quick
pre-publish check - use compliance_check for that. Read-only; deducts 2 credits; runs
asynchronously, poll for the result.

Args:
    text: listing title/bullets/description (required).
    marketplace: marketplace code (default US).
    category: optional category hint.
    lang: zh or en (default en).
    images: optional list of up to 5 data:image base64 strings, each < 4MB.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoen
textYes
imagesNo
categoryNo
marketplaceNoUS

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states the tool is async, read-only, deducts 2 credits, and requires polling for results. It also describes the output as a thorough written risk report, providing valuable behavioral context beyond the schema.

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?

The description is well-organized and front-loaded, with the core purpose stated first, followed by usage guidance, behavior, and a clean Args list. The phrase 'backed by a private 15-year compliance knowledge base' is slightly promotional and not strictly necessary, but it does add credibility context. Overall, it is concise without waste.

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 5 parameters, no output schema, and no annotations, this description covers the essential operational context: what it does, when to use it, what it costs, how it executes (async), how inputs are constrained, and what kind of result to expect. Nothing critical for correct invocation is missing.

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?

Schema description coverage is 0%, so the description must fully compensate for all parameters. It does: text is marked required, marketplace gets a default and purpose, category is described as a hint, lang specifies allowed values (zh/en) and default, and images specifies the exact format (data:image base64), quantity (up to 5), and size limit (<4MB).

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 identifies the tool as a deep compliance audit that produces a written risk report, listing specific coverage areas (prohibited words, IP, category mismatches, GPSR). It explicitly distinguishes itself from the sibling compliance_check by stating this is not for a quick pre-publish check, giving a clear basis for selection.

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

Usage Guidelines5/5

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

The description explicitly states when to use this tool ('when you need a complete, actionable compliance report') and when NOT to use it, directing the agent to compliance_check for quick pre-publish checks. This directly names the alternative, which is ideal for routing.

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

A4.3/5.0
Disambiguation4/5

Most tools map to clearly distinct workflow stages: sentence-to-listing, listing generation, compliance, review analysis, and POA drafting. The main ambiguity is between ai_readiness_check and compliance_check, which both offer fast pre-listing checks with some compliance overlap, though the descriptions try to separate them by purpose.

Naming Consistency3/5

All names are snake_case and readable, but the naming convention is not uniform: analyze_review, fill_from_sentence, generate_listing, and generate_poa are verb-first, while ai_readiness_check, compliance_check, and compliance_scan are noun-first check/scan labels. This mixed pattern is understandable but not predictable.

Tool Count5/5

Seven tools is a well-scoped set for an Amazon listing content and compliance assistant. Each tool has a distinct role in the workflow, and the count feels neither bloated nor thin.

Completeness2/5

The workflow covers generation, compliance, review response, and appeals, but four tools explicitly say they run asynchronously and instruct callers to poll for the result, with no polling or result-retrieval tool present in the set. This creates a dead end for core workflows and will likely cause agent failures unless an unlisted resource mechanism exists.

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