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

No annotations are provided, so the description must convey the operation's nature. 'Check' clearly implies a read-only query and the enumeration of balance, spend, and request count explains what state is being inspected. It does not fully detail error behavior or auth failure cases, but the core behavioral character is transparent.

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 concise sentence with no filler. It front-loads the action and resource, then lists the key outputs. Every word contributes meaning.

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 one optional param, no output schema, and no annotations, the description adequately defines what the tool does and what it reports. It would benefit from a brief note on when to use it relative to open_channel, but nothing critical is missing for direct 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 single optional apiKey parameter is already documented in the schema with format 'channelId:channelSecret' and fallback to BSVKEY_API_KEY. The description adds no additional parameter meaning beyond what the schema already provides.

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 ('Check') with a clear resource ('a prepaid channel') and enumerates the exact data returned (remaining BSV balance, spend, and request count). This is easily distinguished from sibling tools like open_channel or infer.

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 this should be used when you need a channel's balance/usage stats, but it does not explicitly state when to use it versus alternatives, nor does it mention any exclusions or preconditions such as the channel needing to be already open.

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 burden of behavioral disclosure and does a solid job: it reveals that every call is metered and paid per token, that a funded channel key is required, and that the response includes both the completion and a receipt with charges, routed model, and remaining balance. It could add failure behavior for insufficient balance or invalid model, but the key traits are transparent.

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?

Three dense sentences with no filler: the first sentence identifies the action, the second summarizes the return payload, and the third states the prerequisite. Everything essential is front-loaded.

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 paid inference call with complete parameter schema, the description covers the payment model, auth requirement, and return envelope. Even without an output schema, an agent knows what to expect and what it needs to call the tool.

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 the schema already documents all six parameters. The description adds useful context about auth via apiKey or BSVKEY_API_KEY and the receipt contents, but it does not need to compensate for schema gaps, hence the baseline of 3.

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 concrete action, 'Run one metered inference', with a clear resource ('OpenAI-compatible' completion) and payment mechanism (per token in BSV from prepaid channel). This clearly distinguishes it from siblings like list_models, channel_balance, and open_channel, which serve different functions.

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 establishes the context: use this when you want to perform an inference that will consume prepaid BSV credits, and it names the prerequisite of a funded channel key. It does not explicitly name alternatives or when-not-to-use cases, but the sibling names make the decision boundary reasonably clear.

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 full burden, and it does well: it discloses the live pricing behavior tied to the current BSV/USD rate, states the auth requirement explicitly ('No key needed'), and signals the proper call order. It does not describe the exact response shape, but for a simple catalog tool this is a minor gap.

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 short, information-dense sentences. The main action is front-loaded, followed by the key pricing detail and a practical usage instruction. No filler 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?

For a zero-parameter tool with no output schema and no annotations, the description provides the essentials: what is listed, in what unit, with what freshness, auth requirements, and when to call it. An exact return format would be beneficial, but the description is otherwise complete enough to invoke 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?

The tool has zero parameters, so parameter ambiguity is not a concern. The description additionally notes that no API key is needed, which covers the only setup detail an agent might otherwise wonder about.

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 and resource: 'List the models this BSV inference gateway sells.' It clearly identifies what the tool returns and adds a distinguishing detail (live retail price in satoshis per 1,000 tokens) that sets it apart from the sibling 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 instruction 'Call first to choose a model' gives clear sequential context, and 'No key needed' removes a likely prerequisite concern. It does not explicitly name alternatives such as infer, but the intended role as a preliminary discovery step is clear enough.

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 behavioral disclosure. It explains that the actual payment happens externally at the website and that the tool expects a channel key or environment variable, preventing the agent from assuming the tool initiates the payment. It does not cover errors or return behavior, but for an instructional tool this is a minor gap.

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 with no filler: the first states the purpose, the second explains the workflow and prerequisite. Every sentence contributes useful 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?

For a zero-parameter instructional tool, the description covers the essential prerequisite (wallet funding at the website), the input mechanism (channel key or BSVKEY_API_KEY), and the tool's scope. It does not discuss follow-up actions like checking balance, but that is outside this tool's stated job.

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 input schema has zero parameters, so there is little to explain; the description still adds the relevant configuration detail about setting BSVKEY_API_KEY or pasting the returned channel key. This gives the agent practical context beyond the empty schema.

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 the exact function: it explains how to open and fund a prepaid channel. The verb 'explains' plus the resource 'prepaid channel' makes the purpose concrete, and the open/fund scope clearly separates it from the sibling channel_balance tool.

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 a clear workflow: funding is a real wallet-signed BSV payment done at the website first, then the returned key is pasted or supplied via BSVKEY_API_KEY. It does not name alternatives or exclusions, but the usage context is explicit enough.

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