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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds one useful behavioral detail (results sorted ascending by total cost), but says nothing about cost assumptions, currency, or how models are resolved.

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?

A single tight sentence with the action and the output ordering front-loaded. Every clause earns its place with 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?

An output schema exists so return values need no explanation, and annotations cover safety. However, with 0% schema coverage on four required numeric parameters and no usage routing against estimate_monthly_cost, the definition is only minimally sufficient 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 0% and all four parameters are required, so the description carries the full burden. It mentions 'models' and 'monthly costs' but never clarifies the token-volume parameters (input_tokens_per_request, output_tokens_per_request, requests_per_month) beyond what their names already imply, failing to compensate for the coverage gap.

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 (compare) plus resource (monthly costs for multiple models) and even describes the ordering behavior. It implicitly distinguishes itself from the single-model sibling estimate_monthly_cost by scoping to 'multiple models', but never names that alternative explicitly.

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?

'Multiple models' implies this is the multi-model variant versus estimate_monthly_cost, but there is no explicit when-to-use statement, no prerequisites, and no named alternative. Usage is only inferable from the plural scope.

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 the safety profile (readOnly, idempotent, non-destructive), so the bar is lower. The description adds useful context that caching and batch pricing modes affect the result, but says nothing about assumptions (e.g., cached ratio defaults) or output shape.

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?

A single front-loaded sentence with the primary action first and the optional pricing modes trailing. No filler or redundant restatement of the title.

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?

An output schema exists, so return-value explanation is unnecessary, and annotations cover behavior. The description is adequate for a 6-parameter estimation tool, though it leaves the sibling-selection question unanswered.

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 carry the load. It loosely maps to the parameters (request volume, cached-input, batch pricing) but omits units, formats, and the model parameter entirely, so it only partially compensates.

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?

Clear specific verb (estimate) plus resource (monthly token cost) and the driving input (request volume), with optional pricing modes called out. It does not differentiate itself from siblings like get_model_price or compare_models, but the core 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?

No when-to-use, prerequisites, or alternatives are given. An agent cannot tell from this text whether to reach for this versus get_model_price for a single-model lookup or compare_models for a side-by-side. Usage is only implied by the verb 'estimate'.

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, openWorldHint and destructiveHint=false, covering the safety profile. The description adds 'source-linked prices', hinting at provenance of the returned data, but says nothing about lookup failure behavior or external-source reliability that openWorldHint implies.

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?

A single front-loaded sentence with zero filler; the core action and the accepted lookup keys come first.

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 one-parameter read tool with an output schema that documents the return shape, the description covers the essentials. The main omission is behavior when no model matches, which matters given the openWorldHint.

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 carry the param burden. It usefully clarifies that the single 'model' argument accepts either an ID or a display name, but gives no guidance on ambiguity, casing, or partial matching.

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 (find/return) and resource (model, prices) and clarifies the lookup key accepts either an ID or a display name. It does not, however, explicitly differentiate itself from siblings like list_models or price_changes, so an agent must infer the boundary.

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?

Usage is only implied: the description suggests you use this when you have a model identifier and want its price. There is no explicit when-not guidance and no mention of alternatives such as compare_models or price_changes, which overlap in subject matter.

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, idempotentHint=true, openWorldHint=true, and destructiveHint=false, so the agent knows this is a safe, repeatable read operation. The description adds only that models are 'source-linked' and filters are optional; it does not add other behavioral details such as pagination or result ordering, so a baseline 3 is appropriate given the annotation coverage.

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 front-loaded sentence with no wasted words. It immediately conveys the core action and the optional filter behavior, making it appropriately sized for a simple list tool.

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 list operation with rich annotations and an output schema, the description is largely complete. It states the core purpose and optional filters; remaining gaps like provider enumeration and price units are minor because the output schema and structured annotations cover the safety and return-shape concerns.

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 names the filter dimensions (provider and maximum token prices) and implies that both price parameters relate to token pricing, but it does not clarify accepted provider values, whether prices are input/output-specific, units, or currency. It adds some meaning over the bare schema but remains incomplete.

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: 'List source-linked models,' with optional filtering by provider and maximum token prices. It is clear enough to distinguish from siblings like compare_models or get_model_price, but it does not explicitly name an alternative or state how listing differs from those tools.

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 says the tool can optionally filter by provider and maximum token prices, but it gives no when-to-use guidance, no conditions for choosing this over compare_models, get_model_price, price_changes, or estimate_monthly_cost, and no exclusions. Usage context is left entirely to inference.

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, openWorldHint and destructiveHint=false, so safety is covered. The description adds genuinely new behavioral facts: the result is capped at 20, ordered newest-first, and each event is source-linked. It does not explain what the 'since'/'provider' filters do behaviorally.

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?

A single front-loaded sentence with no filler; the limit and ordering constraints are stated up front where an agent will read them.

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?

An output schema exists, so return values need no explanation, and annotations carry the safety profile. The remaining gap is parameter meaning: two undocumented filters at 0% schema coverage, especially the open-ended 'provider' string, leave the agent guessing.

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 carries the full burden for the two parameters — and it says nothing about 'since' or 'provider'. A caller cannot learn from either source what values 'provider' accepts or whether 'since' is inclusive.

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 ('List') and resource ('source-linked price-change events') with a clear scope ('up to 20 newest'). It is distinguishable from get_model_price or compare_models, but it never explicitly contrasts itself with those siblings.

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?

There is no when-to-use statement, no exclusions, and no reference to the sibling tools. An agent must infer that this is a changelog/feed-style tool purely from the word 'events'.

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