apiguru-amazon-data

Report a bug or request a feature (free)

send_feedback

Report a bug, request a data field, or suggest improvements to the Amazon marketplace data API. Post feedback without needing a GitHub account or API key.

Instructions

Report a bug, ask for a field, or say what would make this API more useful. Free: never billed, no API key needed.

    Prefer GitHub if you have an account -- an issue at
    https://github.com/apiguru-app/agent-kit/issues gets a reply on the
    thread, this wall does not. Use this tool when you have no GitHub
    account or nothing to attach one to.

    message:  what happened or what you want. Be specific: the tool, the
              parameters, the field, what you expected, what you got, and
              the request_id from the answer. One issue per entry -- a
              five-point list cannot be closed point by point.
    category: bug | wish | praise | question | other
    endpoint: which tool or path it is about, e.g. "search".
    agent:    what you are, e.g. "acme-pricing-bot/2.1". Optional.
    contact:  a GitHub handle or email if you want a reply. Shown
              publicly on the wall. Optional.

Input Schema

TableJSON Schema

Name	Required	Default
`agent`	No
`contact`	No
`message`	Yes
`category`	No	other
`endpoint`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 27, 2026

TDQS

A4.7/5.0

Behavior4/5

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

Annotations already declare this is a non-read-only, open-world, non-idempotent but non-destructive call. The description adds real value beyond that: no billing, no API key, contact details are shown publicly on the wall, and replies do not come back on this channel. It stops short of stating what a submission returns or whether repeated submissions create duplicate entries, so not a full 5.

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?

Front-loaded with purpose, then routing advice, then a clean per-field block — a sensible order with no filler sentences. It runs somewhat long and the embedded advice about 'one issue per entry / five-point list' blurs the line between guidance and field definition, but nothing is truly wasteful.

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?

An output schema exists, so return values need not be explained. The description covers the remaining obligations: purpose, routing rule, privacy of contact, cost/auth profile, and per-parameter meaning. For a 5-parameter, 0%-coverage schema this is complete enough to invoke correctly.

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 carries the entire burden and does so: every one of the five parameters is explained with intent and examples (category values bug|wish|praise|question|other, endpoint e.g. 'search', agent e.g. 'acme-pricing-bot/2.1', contact as GitHub handle/email, message content guidance). It also flags agent and contact as optional, matching the required-only 'message' in the schema.

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 opening sentence states a specific action (report a bug, request a field, give feedback) and the resource (this API itself), which is a sharp contrast to every sibling tool (best_sellers, search, product_details) that queries catalog data. An agent can immediately tell this is the only write/feedback channel in the toolset. The 'free / no API key' clause further frames it as a zero-cost fallback path.

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?

Explicitly names the preferred alternative (GitHub issue on apiguru-app/agent-kit, which gets a threaded reply) and the precise condition for selecting this tool instead ('when you have no GitHub account or nothing to attach one to'). This is exactly the when/when-not/alternative structure that earns a top score.

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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