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Goppa

Read your SEO fixes

get_seo_fixes
Read-onlyIdempotent

The SEO fixes Goppa prepared for your pages (titles, meta descriptions, image text): the ones waiting for your approval with the current and proposed text, the ones applied on your site, and the product questions. Read-only: approving happens in Goppa.

Input Schema

NameRequiredDescriptionDefault
siteNoOne of your sites in Goppa, by domain (example.com). Required when the account has more than one site: without it, the answer lists the sites to choose from. With a single site it can be left out.
cursorNonext_cursor from the previous page, to read the next 10 items.

Output Schema

NameRequiredDescriptionDefault
noteNo
pageNo
ruleNo
siteNo
as_ofNo
errorNo
savedNo
stateNo
countsNo
marketNo
periodNo
reasonNo
sampleNo
missingNo
partialNo
summaryNo
languageNo
availableNo
data_statusNo
next_actionNo
evidence_idsNo
open_in_goppaNo
site_requiredNo
workspace_urlNo
left_this_monthNo
recently_appliedNo
sites_in_accountNo
untrusted_fieldsNo
product_questionsNo
fixes_paused_by_youNo
pages_read_from_your_siteNo
waiting_for_your_approvalNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

The annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint, so the safety profile is covered. The description adds meaningful behavioral context by listing the fix statuses included and clarifying that approval is handled elsewhere, though pagination behavior is left to 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 front-loaded and dense with useful categorization, with no filler. The first sentence is somewhat long and list-heavy, but every clause contributes to scope or content.

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?

With rich annotations, full schema descriptions, and an output schema, the description provides enough context to invoke the tool correctly. Minor gaps around pagination and sibling-tool routing are covered by structured fields or handled elsewhere.

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 description coverage is 100%, so the site and cursor parameters are already well documented in the schema. The description adds no additional parameter semantics, which is acceptable given the complete schema coverage.

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 states a specific resource and scope: SEO fixes prepared by Goppa, including pending, applied, and product-question items. It is clear what the tool returns, but it does not explicitly distinguish itself from related siblings such as get_fixes_to_apply or report_fixes_applied.

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?

It clearly establishes that this is a read-only view and that approval happens in Goppa, which is a useful usage boundary. However, it does not explicitly say when to choose this tool over the closely related fixes/apply siblings, leaving that inference to the agent.

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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