Price list
pricingEvery endpoint this server fronts, with its exact per-call USD price (x402, USDC on Base) and a one-line summary, read live from the route table. Free.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
pricingEvery endpoint this server fronts, with its exact per-call USD price (x402, USDC on Base) and a one-line summary, read live from the route table. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses that data is read live from the route table and that the call is free, but it doesn't address authentication, rate limits, or response format beyond a one-line summary.
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 a single, well-structured sentence that front-loads the essential information: scope, content, and cost.
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 no-param tool without an output schema, the description covers the key aspects: what it returns, that it's live, and that it's free. Minor gaps exist, such as response structure, but overall it is sufficient.
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 the description needn't explain parameter semantics. The baseline of 4 applies, as there is no gap to compensate for.
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 that it lists every endpoint with its exact per-call USD price and a one-line summary, making the tool's purpose unambiguous and distinct 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?
Usage is implied as a reference for endpoint pricing, but the description does not explicitly say when to use it (e.g., before calling any endpoint) or contrast it with alternatives.
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 targets a distinct resource and operation: coverage and pricing are meta, find_data searches endpoints, request_data handles missing data, and the data tools are clearly separated by type (FX, holdings, insider, IPO, macro, SEC filings, security holders). Even the three holdings-related tools have clear boundaries: manager_holdings gives a portfolio, holdings_changes gives changes vs prior quarter, and security_holders gives holders by CUSIP.
All names use lowercase with underscores, which is consistent, but the pattern mixes nouns (coverage, pricing, fx_rate, macro_series) and verb_noun pairs (find_data, request_data). This is readable but not a fully predictable verb_noun convention as seen in well-structured servers.
With 12 tools, the count is well within the ideal range for a data-access server, covering discovery, metadata, pricing, and a broad set of financial datasets without feeling bloated.
The domain is financial data access, and it covers key areas: SEC filings, institutional holdings, insider activity, IPO pipeline, macroeconomic series, FX rates, and data discovery. The main gap is a lack of a full-text filing retrieval tool, but sec_filing_section provides sections, and request_data allows filling missing coverage.