providers

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

No annotations are provided, so the description carries the full transparency burden. It does disclose two useful behavioral traits: that all plans are included and that plans are sorted cheapest first per provider. However, it does not describe the return format, pagination behavior, or explicitly state that the operation is read-only.

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 well-structured sentence that leads with the primary action and resource, then adds scoping and ordering details. Every phrase adds value and there is no filler or redundant information.

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?

The tool is simple (one parameter, no output schema), so the description covers the core purpose and sorting behavior. Still, with no output schema and no annotations, the lack of any return-value description makes it less complete than it could be for an agent trying to predict the tool's exact result shape.

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 0% and the only parameter, 'brands', has no description. The tool description adds that 'brands' identify providers and implies at least two are needed, but it does not clarify whether these are names, IDs, slugs, or exact values. This only partially compensates for the missing schema documentation.

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 uses a specific verb ('Compare') and resource ('providers'), and adds important scope details: 'two or more', 'all their plans', and 'cheapest plans first per provider.' This clearly distinguishes it from sibling tools like find_providers, get_provider, and list_providers.

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 description implies when to use this tool—whenever providers need to be compared—but it provides no explicit guidance about when not to use it or which sibling tool should be used instead for other tasks. There are no named alternatives or exclusions.

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?

With no annotations provided, the description carries the behavioral disclosure burden. It adds meaningful semantics beyond the schema: boolean filters are strict ('verified present'), max_monthly_price uses a normalized 'cheapest per-month equivalent,' and plan_type has enumerated values. This helps avoid misinterpreting filter behavior. Some traits (e.g., behavior with no filters, result ordering) are not disclosed, so it is not perfect.

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 three concise sentences, each earning its place: the first states the core purpose, the second clarifies boolean and price filter behavior, and the third defines plan_type values. It is front-loaded, avoids fluff, and is easy to scan.

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?

The tool has 10 parameters, no output schema, and no annotations, requiring a fairly complete description. It covers the most important filter semantics and gives enough to invoke the tool correctly, where the result is clearly a list of matching providers. However, it does not mention default behavior (no filters provided), result size/limits, or any specifics about the response format, leaving some gaps in the full usage context.

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 0%, so the description must compensate. It does so by explaining the ambiguous parameters: the general boolean filter rule covers all six booleans, and max_monthly_price and plan_type get explicit semantic clarification. The remaining parameters (min_storage_gb, free_only, lifetime_only) have self-explanatory names/units, so the description effectively covers the meaningful semantics of nearly all 10 parameters.

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 opens with 'Find cloud storage plans matching filters,' which uses a specific verb ('Find'), a clear resource ('cloud storage plans'), and a clear scope ('matching filters'). This distinguishes it from siblings like list_providers (unfiltered listing) and compare_providers (comparing), making the tool's role immediately obvious.

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 description provides clear context on when to use the tool: whenever you need to find/filter storage plans rather than compare or retrieve a specific one. It also explains how key filters behave ('Boolean filters require the feature to be verified present; max_monthly_price compares against the cheapest per-month equivalent'), giving practical usage guidance, though it does not name explicit alternatives.

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?

No annotations provided, so description carries burden. It discloses that facts are 'verified' and includes source URLs, which is useful. But it doesn't disclose if data is cached, freshness, or any limits. The term 'verified' adds context beyond 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?

Single concise sentence with essential information, no redundancy. Efficiently communicates purpose and key distinguishing feature (source URLs). Could be slightly improved with explicit delimiter but overall well-structured.

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?

Tool is relatively simple (2 params) but has no output schema. Description mentions per-field source URLs and verification, which is good. However, it doesn't describe the structure of returned data or any limitations, and with no annotations, a bit more behavioral context would help.

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 0%, so description must add meaning. It mentions 'all plans, or one named plan', which explains the optional 'plan' parameter. However, does not clarify 'brand' semantics beyond schema, and no format details for plan names or brand identifiers.

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?

Description clearly states it retrieves full verified facts for provider plans, optionally for one named plan, with source URLs. It distinguishes from siblings like find_providers/list_providers by focusing on detailed per-plan data, though it doesn't explicitly differentiate from compare_providers.

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?

Implies usage for retrieving detailed facts for a specific provider/brand, and the optional plan parameter suggests use when one plan is needed. However, no explicit guidance on when to use this vs compare_providers or list_providers, and no mention of prerequisites or 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?

With no annotations provided, the description bears full responsibility for behavioral disclosure. It states that the tool returns 'every' plan and specifies the returned fields, which provides transparency about the scope and content. However, it does not mention whether the list is sorted, limited, or paginated, which is a minor gap for a list-all tool, but acceptable for such a simple operation.

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, concise sentence that immediately states the primary action ('List every...') and the payload details. It contains no filler or redundant information, and the front-loading is optimal for quick comprehension.

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 zero-parameter list tool without an output schema, the description sufficiently addresses what the tool does and its output content. It could hint at whether results are sorted or if any plans might be excluded, but given the simplicity, the coverage is adequate. The sibling context is not discussed, but that is not strictly required.

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 tool has zero parameters, so the baseline for parameter semantics is 4. The description adds context about what the returned data includes, but since there are no parameters to document, it appropriately does not expend space on parameter details. The schema coverage is 100%, meaning no undocumented parameters exist.

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 verb 'List' clearly specifies the action, and the resource is precisely described as 'every cloud storage plan we track' with explicit enumeration of included data (prices, storage, security flags, verification date). This distinguishes it from sibling tools like get_provider (single plan) or compare_providers (comparison), so the purpose is unambiguous.

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 description implies use when a complete overview of all plans is needed, but it does not explicitly state when not to use it or contrast with alternatives like find_providers (likely for searching) or price_history (for historical data). The context is clearest from the tool's purpose, but no explicit guidance is given.

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?

With no annotations, the description carries the burden of disclosing behavior. It mentions that history accumulates as plans are re-verified, which gives insight into data freshness, and states ordering (newest first). However, it does not explicitly confirm it is a read-only operation or describe any side effects, leaving some ambiguity.

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 succinct, comprising two sentences that front-load the core purpose and ordering, followed by a useful note on how history accumulates. No extraneous words or unnecessary details.

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 simple tool with no output schema, the description covers the essential aspects: it returns dated snapshots, is time-series specific, and clarifies data accumulation. It does not detail the return format or potential limits, but given the simple nature and no annotations, it is reasonably complete.

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 description does not explain the meaning or relationship of the 'plan' and 'brand' parameters, and the schema provides no descriptions (0% coverage). The phrase 'for one plan' implies 'plan' is central, but the role of 'brand' is entirely unexplained, offering no added value beyond the bare parameter names.

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's function: retrieving price snapshots over time for a specific plan, with explicit ordering (newest first). This distinguishes it from siblings like compare_providers or list_providers, which focus on provider comparisons or listings.

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 description clearly implies when to use this tool (when historical price snapshots for a single plan are needed) and emphasizes 'one plan', setting it apart from multi-plan tools. However, it does not explicitly mention alternatives or state when not to use it, so it lacks explicit exclusions.

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