SEO Records Corrector

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

Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint), it discloses that the page is read, corrected in memory, and forgotten, so no persistent changes occur. It also explains what is returned, including corrections with source and exact HTML tags, before/after Google snippets, and issues left to the author, plus the paid access requirement.

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

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

The purpose is front-loaded in the first clause, and every sentence adds useful information about outputs, data handling, and access requirements. The long enumeration of correction types is dense but valuable for an agent, and there is no filler.

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

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

With no output schema, the description carries the burden of explaining return values, and it does so thoroughly: corrections with values, sources, and exact HTML tags, Google snippets before and after, and remaining author issues. It also covers the in-memory processing model and the access pass requirement, making it complete for correct invocation.

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

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

Schema description coverage is 100%, and the schema already documents both url and access_key. The description adds context that a public page is needed and that an access pass is required, but it provides no syntax or format details beyond the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

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

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

The description states a specific verb and resource: it runs the SEO Records correction engine on a public page and returns the corrections it would apply. The enumerated output fields make the tool's purpose unambiguous. It stops short of naming or contrasting with the sibling tool get_automatic_fix_offer, which keeps it from a 5.

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

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

It gives clear context for use: a public page, corrections returned rather than applied, and an access pass required. There are no explicit when-not-to-use rules or direct comparisons to the sibling alternative, so it does not reach 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so safety is covered. The description adds genuinely useful behavioral content beyond that: the response includes product descriptions, prices and secure Stripe payment links, which tells the agent what it will get back without an output schema.

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

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

One front-loaded sentence that is readable, but it is padded with marketing content — the same €199/year price repeated twice and a docs URL — that is not needed to select or invoke the tool correctly.

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

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

For a trivial one-optional-param read tool with annotations covering safety, the description is adequate, but it lacks any indication of the shape of the returned offer list (one product vs many, ordering, currency) which matters since there is no output schema.

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

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

Schema description coverage is 100% and the single language enum parameter is fully documented in the schema (default en). The description never mentions the language parameter, so it adds no meaning beyond what the schema already provides; baseline 3 applies.

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

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

States a specific verb and resource: returns SEO Records products that apply corrections automatically, listing what each offering does, its price, and a payment link. An agent can tell this is an offer/commerce lookup rather than the sibling fix_page_seo action, though fix_page_seo is never named for contrast.

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

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

No statement of when to call this versus fix_page_seo, and no prerequisites or exclusions. The commercial framing implies the agent should use it when a user asks about automated fixes, but that inference is left entirely to the reader.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.