Electronic Code of Federal Regulations title status: latest amendment date and issue date for one CFR title. $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 provided, the description carries the full burden. It discloses the cost per call, payment method (x402 USDC on Base), and the response includes a provenance chain and Ed25519 attestation. This goes well beyond basic schema information, though it does not explicitly state read-only behavior or potential side effects, which is acceptable for a lookup tool.
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, dense sentence that fronts the core purpose ('title status'), then adds cost, payment method, and response details without redundancy. Every element earns its place, and the most important information is presented first.
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 tool lacks an output schema, and the description does not specify the id parameter's format or provide guidance on obtaining a quote by omitting payment. It mentions the provenance chain and attestation but not the full response shape. For correct invocation, an agent would need to infer or discover the id format, leaving a significant gap.
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 only describes the 'payment' parameter; the required 'id' parameter has no schema description. The tool description does not explain what format the id should take (e.g., CFR title number) or how it maps to 'one CFR title'. While payment benefits from cost/payment method context, the id remains undefined, and the description fails to compensate for the 50% schema coverage gap.
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 the tool's function: to provide the latest amendment date and issue date for one CFR title. This is specific and distinguishes it from sibling tools like fedreg_doc_lookup (which deals with individual federal register documents). It also mentions the cost and attestation, further clarifying the tool's unique value.
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 conveys the exact use case (checking a CFR title's status) without ambiguity. While it does not explicitly contrast with alternatives or state when not to use it, the tool's specificity makes confusion unlikely. The guidance is implicit but clear enough for an agent to select it appropriately.
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.