FDA recall counts for one US state, grouped by classification and product type, computed over the current enforcement dataset. $0.02 per call via x402 (USDC on Base); response includes a provenance chain and an Ed25519 attestation.
| Name | Required | Description | Default |
|---|---|---|---|
| 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 burden, and it does disclose useful non-obvious behaviors: the $0.02 per-call cost, the x402/USDC-on-Base mechanism, and the response containing a provenance chain and Ed25519 attestation. However, it leaves unexplained how 'one US state' is determined and does not clarify the payment handshake beyond what the schema already says.
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 with no wasted words: the first delivers the core function and scope, the second packs pricing, payment rail, and response attestation details. Everything present earns its place.
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 does a reasonable job for a single-parameter paid API, but a critical gap remains: it claims to operate 'for one US state' with no state parameter and no explanation of how that state is provided. There is also no output schema, and while the provenance chain is mentioned, the overall return structure is not described.
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 for the only parameter, payment, so the baseline is 3. The description adds cost and dataset context but no additional meaning about the payment parameter's encoding, format, or required workflow beyond what the schema already documents.
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 states a specific action ('recall counts'), a resource ('FDA recalls'), and a scoping detail ('for one US state'), plus grouping dimensions ('classification and product type'). It stops short of 5 because it never explains how the state is actually selected given the schema only exposes a payment parameter, and it doesn't explicitly differentiate itself from the sibling fda_recall_lookup.
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 gives no guidance on when to choose this tool instead of fda_recall_lookup or the CPSRC recall summaries. It mentions the payment/quote flow but no usage context, exclusions, or comparison to 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 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.