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call_api

Call an API on the bolthub marketplace with automatic L402 Lightning payments. Preview costs first, set a budget, and get the response with cost info.

Instructions

Call an API endpoint on the bolthub marketplace. Handles L402 Lightning payments automatically. Use get_api_details or preview_cost first to check pricing. Returns the response along with cost and budget information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNoJSON request body for POST/PUT/PATCH requests
pathYesThe endpoint path (e.g. '/v1/history/candles')
slugYesThe API slug (e.g. 'btc-intel')
methodNoHTTP method — defaults to GET
headersNoAdditional HTTP headers
query_paramsNoQuery parameters as key-value pairs
max_cost_satsNoMaximum sats to pay for this request. If the invoice exceeds this amount, the call is refused and nothing is paid.
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses automatic L402 payment handling and that it returns cost and budget info. However, it does not mention failure modes, rate limits, or what happens when payment fails, leaving some behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences long, front-loaded with the core purpose, and contains no unnecessary words. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (7 params, no output schema), the description provides key context: payment handling, suggestion to check pricing first, and return info. It is nearly complete but could mention expected response format or error handling for full completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so each parameter is described in the schema. The tool description itself does not add additional parameter semantics beyond what is in the schema, meeting the baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it calls an API endpoint on the bolthub marketplace and handles L402 payments. It distinguishes from siblings like get_api_details (provides API info) and preview_cost (checks pricing), making the tool's purpose specific and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly advises using get_api_details or preview_cost first to check pricing, providing clear context for when to use this tool vs alternatives. It lacks explicit when-not-to-use guidance but is sufficient.

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

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