get_workflow_endpointBuild the exact paid HTTP endpoint, method, starter-credit cost, and example body for a premium Blocksize workflow. This is free and read-only; it does not fetch live data, charge credits, or start x402.
| Name | Required | Description | Default |
|---|---|---|---|
| product | Yes | Premium Blocksize workflow product to prepare. |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes beyond the annotations by specifying the output content (endpoint, method, cost, example body) and clarifying it does not fetch live data or charge credits. This adds meaningful behavioral context not covered by readOnlyHint or idempotentHint alone.
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, front-loaded with the primary action, and followed by a succinct clarification. No wasted words, and the structure makes the purpose immediately clear.
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 tool with a rich output schema and extensive annotations, the description fully covers what is needed. It explains what is built and what is not done, making it complete for its simple complexity.
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 100% coverage with a clear enum description for 'product'. The description does not add significant parameter-level detail, but the schema is sufficient, so the baseline of 3 applies.
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 'Build' with a clear resource ('exact paid HTTP endpoint, method, starter-credit cost, and example body') for premium Blocksize workflows. It distinguishes itself by stating it does not fetch live data or charge credits, which separates it from sibling data 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?
Provides clear when-not guidance by stating it is free, read-only, does not fetch live data, charge credits, or start x402. This signals it is for preparing an endpoint rather than executing. However, it does not explicitly name alternative sibling tools like get_market_data_endpoint, so it lacks full alternative differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct primary purpose, but search and search_pairs overlap in discovery, and get_market_data_endpoint vs get_workflow_endpoint both build endpoints. Descriptions clearly differentiate them, so confusion is unlikely.
All tool names follow a consistent verb_noun pattern with snake_case (get_, list_, search_, fetch). The naming is predictable and uniform across the set.
With 8 tools covering search, catalog, pricing, and endpoint building, the count is well-scoped for a market intelligence discovery server. No redundancy or bloat.
The tools cover documentation search, instrument discovery, product/pricing info, and endpoint construction. The only minor gap is not executing actual paid data fetches, but that is intentionally left to the generated HTTP endpoints.