searchSearch Blocksize documentation and catalog metadata by keyword. This free read-only search returns document and instrument ids for fetch; it does not return live prices or start payment.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Documentation or catalog search query, such as pricing, quickstart, credits, x402, Solana, Base, BTC, or VWAP. |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate safety (read-only, idempotent). Description adds 'free', 'returns ids for fetch', and explicitly excludes live data/payment actions, providing useful behavioral context beyond the 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?
Two efficient sentences, front-loads purpose, then clarifies exclusions. No wasted words.
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?
With a single parameter, output schema present, and annotations covering safety, the description sufficiently covers usage context. It explains the tool's role in the larger workflow (returning ids for fetch) and its limitations.
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 schema fully describes the single 'query' parameter with length constraints and example queries, achieving 100% coverage. The description adds no additional parameter-level detail, so baseline 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?
Clearly states it searches Blocksize documentation and catalog metadata by keyword. Distinguishes itself from sibling tools by specifying it returns document/instrument ids for fetch and explicitly excludes live prices and payments.
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 context that this is the appropriate tool for keyword searches of docs/catalog, and explicitly states it does not return live prices or start payment, signaling when not to use it. Does not name alternative tools by name but gives enough guidance.
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.