US Congress bill record by congress, type and number: title, sponsor, latest action, policy area and origin chamber. $0.005 per call via x402 (USDC on Base); response includes a provenance chain and an Ed25519 attestation.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| payment | No | Encoded x402 X-PAYMENT header value. Omit to receive the payment requirements (free quote). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden and does disclose meaningful non-obvious behavior: the per-call cost, x402 payment via USDC on Base, the provenance chain, and the Ed25519 attestation. It does not cover rate limits or authentication details, but the key behavioral traits are surfaced.
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, tightly packed sentence that leads with the core purpose and then adds cost and response details. Every clause contributes useful information, with 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?
The description covers purpose, cost, payment behavior, returned fields, provenance, and attestation, which is substantial for a two-parameter lookup tool. However, without an output schema or an explicit format/example for constructing the required id, an agent may not be able to invoke the tool correctly on the first attempt.
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 payment parameter is well documented in the schema, and the description adds context about the pay-per-call mechanism. However, the required 'id' parameter is only vaguely described as representing congress, type, and number; the exact encoding/format is not specified, leaving an important gap at 50% schema coverage.
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 names a specific resource ('US Congress bill record') with the exact lookup dimensions (congress, type, number) and enumerates the returned fields (title, sponsor, latest action, policy area, origin chamber). This clearly differentiates it from the sibling lookup tools, which are all in unrelated domains.
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 makes the intended use case clear: retrieving a specific congressional bill by its identifying components. It does not explicitly exclude alternatives, but the sibling tools cover different topics, so the applicable context is unambiguous.
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 unique dataset and operation: lookups by ID, summary aggregations, time series, or search. Even tools with similar descriptors (e.g., FMRArea lookup vs. search, FDA vs. CPSC recalls) are clearly separated by resource and output type.
All tool names are lowercase snake_case and mostly follow a `domain_resource_kind` pattern such as `fda_recall_lookup` and `cpsc_recall_monthly_summary`. A few outliers like `bank_profile_lite`, `cpi_us_monthly`, and `us_debt_to_penny` break the dominant suffix convention but remain readable.
24 tools is on the high side for a single server, but this appears to be an aggregator of many independent public datasets, so each tool represents a distinct data source and has a purpose. It is slightly above the ideal ergonomic range but not bloated or redundant.
As a read-only attested-data lookup service, the set provides good coverage with both point lookups and aggregate summaries across many domains. The main gaps are the lack of a catalog/discovery endpoint and search support for most identifier-based lookups, but agents can work around those with known identifiers.