verified-codes

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

Annotations already signal a safe read-only operation, so the description does not need to cover destructive or side-effect behavior. It adds useful context about matching by name or slug and the composition of the returned record, though it does not disclose edge-case behaviors like case sensitivity or missing brands.

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?

Two sentences, front-loaded with the return value and followed by matching guidance. Every clause earns its place; no filler or restatement.

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 low-complexity single-parameter lookup, the description, input schema, output schema, and read-only annotations together cover what the agent needs. The validation rule is clear, examples are provided, and nothing important is missing.

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 coverage is 100%, and the property description already provides examples ('kraken' or 'Bybit Card'). The description repeats these examples but does not add significant new parameter-level meaning, so the baseline of 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?

The description states a specific action ('Returns the full verified-code record') and a clear scope ('for one brand'), and enumerates what fields are included. The singular-resource scope also distinguishes it from siblings list_brands and search_codes without ambiguity.

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 clearly establishes the lookup context: use when you need one brand's complete verified-code record, matched by brand name or slug. It does not explicitly name alternatives or exclusion conditions, but the one-brand targeting makes the intended use evident.

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 establish readOnlyHint=true and openWorldHint=false, so the safety profile is handled. The description adds that the code field is optional ('if any') and enumerates the category filter values, but does not disclose pagination, result limits, or other behavioral nuances.

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 description is a single sentence that front-loads the return shape and immediately provides the filter options. There is no filler or redundant restatement of the tool name.

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 single optional parameter with an output schema and read-only annotations, the description is largely sufficient. It lacks a brief note on how 'all brands' relates to 'verified codes' and whether results are paginated, but these are minor given the tool's simplicity.

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?

The schema describes the category parameter with only an example, while the description explicitly lists all nine valid category values. This adds real meaning beyond the schema, even though schema coverage is 100%.

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 clearly states the tool returns a brands array with category, offer, and code, and identifies the optional category filter. It does not explicitly differentiate itself from the sibling tools get_code and search_codes, though the resource emphasized is brands rather than individual codes.

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?

The usage is implied: list all brands, optionally filtered by category. There is no explicit guidance about when to prefer list_brands over get_code or search_codes, nor any exclusions, so the agent must infer the appropriate context.

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=true and openWorldHint=false, covering the safety and completeness profile. The description adds that results are 'matching verified-code records,' but does not discuss ordering, result limits, or empty-result behavior. With annotation coverage, a 3 is appropriate.

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 tightly written sentence that front-loads the action and scope, then illustrates with examples. Every clause carries useful information and there is no repetition of the schema or annotations.

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 single-parameter, read-only search tool with full schema documentation and an output schema present, the description provides everything an agent needs to invoke it correctly. The examples and scope statement remove ambiguity about query intent.

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 coverage is 100%, so the 'query' parameter is already documented as 'Search terms.' The description goes beyond this by explaining the free-text nature and giving three diverse example queries that clarify expected phrasing and scope. This adds genuine value.

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 ('search'), resource ('verified-code records'), and search surface ('brands, categories and offers'). The title and description clearly differentiate it from siblings: get_code is for looking up a specific code and list_brands is for listing brands, not free-text searching.

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?

Provides clear usage context with concrete examples ('stock perps discount', 'esim', '20% off exchange') that tell an agent what kind of queries belong here. It does not explicitly name when-not-to-use it or point to get_code/list_brands as alternatives, so it stops short of a 5.

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