BridgeNode MCP

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

Despite the annotations being present (all false), the description adds significant behavioral context beyond them: the x402 payment requirement, 402 retry flow, non-streaming responses, and max_tokens clamping. This is exactly the kind of disclosure that helps an agent understand side effects and constraints.

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 dense but well-structured, with each sentence serving a purpose. It front-loads the core action, then layers payment, routing, and usage guidance. No fluff or repetition.

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 description covers all critical aspects: payment flow, routing modes, mutual exclusivity, default behavior, and an alternative tool. With an output schema present, return values are adequately specified. This is a complete, production-quality description.

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%, so baseline is 3. However, the description adds valuable semantics: mode values are explained (auto/eco/premium routing), the model-wins precedence is stated, and max_tokens default and clamping behavior are specified. This goes well beyond the schema field descriptions.

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 a specific verb+resource: 'Send a chat completion request to any supported model.' It clearly distinguishes itself from sibling tools by explicitly recommending list_models for inspecting models and prices. The purpose is unambiguous and not a tautology.

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 explicit guidance on when to use this tool ('Use this tool to generate text') and directs users to list_models for pre-inspection. It also explains the required mode/model choice, mutual exclusivity, and precedence rules, giving clear decision criteria.

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?

Beyond the annotations (readOnlyHint, idempotentHint), the description adds non-obvious behavioral details: free, no authentication, no external calls, computed locally from server pricing config, and idempotent results. This significantly enriches the annotation-provided safety profile. No contradiction found.

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 front-loaded with the core purpose, then safety, usage, and parameter details. Every sentence earns its place, providing a logically organized and highly informative text without redundancy.

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?

Given the presence of an output schema, the description appropriately avoids explaining return values. It covers usage context, safety, parameter semantics, and relationship to sibling tools, making it fully adequate for an agent to select and invoke the tool correctly.

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?

Though schema coverage is 100%, the description adds crucial semantics: defines mode values (auto/eco/premium), explains mutual exclusivity and that model wins if both are provided, clarifies that one of mode/model is required, and notes max_tokens is billed upfront. This goes well beyond the schema descriptions.

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 estimates the USDC cost of a chat completion request before paying. It uses a specific verb ('Estimate') and resource ('chat completion request'), and distinguishes itself from sibling tools like chat_completions (paid) and list_models (model listing).

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?

Explicitly states when to use this tool: 'Use this tool to check the exact price ... before calling the paid chat_completions tool.' It also explains when to use mode vs model and notes mutual exclusivity and precedence, providing clear guidance on alternative approaches.

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?

The description adds significant context beyond annotations: free, no authentication required, data served from server's local config, no filtering/pagination/config, identical results on repeat calls. It reinforces read-only and idempotent behavior with concrete explanations. No contradiction with annotations.

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 appropriately sized for the tool's simplicity. It front-loads the core purpose in the first sentence, then provides necessary detail in a logical order (behavior, parameters, usage, exclusions). Every sentence earns its place without waste.

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 an output schema, so return values are covered. The description is complete for a zero-parameter read-only tool: it covers what it lists, the data source, idempotency, lack of filtering, and how it differs from sibling tools. No gaps remain.

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?

There are zero parameters, which gets a baseline of 4. The description adds 'Accepts no parameters: calling it without arguments returns the complete catalog' – confirming the semantic of the empty input. This is sufficient; no additional parameter information is needed.

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 starts with 'List available models and their prices' – a clear verb+resource statement. It explicitly distinguishes from siblings by saying 'Do not use it to generate text (use chat_completions) or to estimate a specific request's cost (use get_price_estimate).' This makes the tool's purpose unmistakable.

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?

Explicit usage guidance is provided: 'Use this tool to inspect models and prices before calling the paid chat_completions tool.' It also gives direct exclusions: 'Do not use it to generate text (use chat_completions) or to estimate a specific request's cost (use get_price_estimate).' This clearly states when to use and when not to use, naming specific alternatives.

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