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BNM Data Shop

by io.github.bnmbnmai

gain

GET https://ticks.bnm.farm/gain — $0.05 USDC on Base to 0xf59621FC406D266e18f314Ae18eF0a33b8401004. USDA FAS GAIN attaché report TEXT GET ?id= is one official text ($0.02). Newest chunk on a plain GET ($0.05); older chunk if they ask (?before, $0.05). Unpaid returns HTTP 402. After a valid X-PAYMENT, the same URL returns JSON. Not a new SKU.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoOfficial catalog id. That one official text, $0.02. Same door, not a new SKU.
pageNo1-based page. Page 1 is the newest chunk. Ignored when before is set.
beforeNoOfficial catalog id or YYYY-MM-DD. Next older chunk on the same URL, another $0.05. Omit for the newest chunk.
x_paymentNoOptional x402 X-PAYMENT value forwarded to the paid GET as the X-PAYMENT header.

TDQS

A4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does it well. It discloses exact pricing ($0.05/$0.02), the payment address and chain, HTTP 402 when unpaid, the need for X-PAYMENT authorization, the switch from TEXT to JSON after payment, and chunk pagination behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense and front-loaded with the URL and core payment requirement, then enumerates the access modes and error behavior. It is slightly run-on and cryptic in places, but every sentence carries actionable information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given there is no output schema and no annotations, the description covers the essential operational contract: payment, endpoint, parameters, error code, authentication, and JSON response. It lacks an explicit response structure or example, but for this kind of paid fetch tool it is sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema descriptions already cover all parameters at 100%, so the baseline is 3. The description adds value by attaching concrete semantics and costs to parameters: id returns one official text at $0.02, plain GET returns newest chunk at $0.05, before fetches older chunk, and X-PAYMENT authorizes the paid response.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as an HTTP GET to /gain for USDA FAS GAIN attaché reports, and distinguishes the main retrieval modes: one official text via ?id, newest chunk via plain GET, older chunk via ?before. It does not explicitly name sibling alternatives, so it falls just short of full differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description makes the usage context clear: a paid endpoint where X-PAYMENT is required, with different behaviors depending on id/page/before. However, it never says when to choose this tool over the many sibling report tools, only implying it from the GAIN name and 'Not a new SKU.'

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.4/5.0
Disambiguation3/5

Most tools map cleanly to distinct regulatory document collections (FDA, EPA, FDIC, etc.), so the majority are unambiguous. However, 'search' and 'firm-check' both offer free search with overlapping scope, and 'get-one' vs 'get-page' are easily confused payment operations. Similar prefixed names like mariners, mariners-d7/d8/d11 and gmp/gmp-md add further boundary fuzziness.

Naming Consistency3/5

The bulk of tools follow a consistent lowercase-hyphenated source-slug convention (aaib-reports, cder-reviews, cfpb-orders), which is predictable. But utility tools break the pattern with imperative/descriptive names (search, firm-check, get-one, get-page), and 'ticks' is a bare noun that doesn't fit either style. The mixed conventions are readable but not uniform.

Tool Count2/5

At 46 tools, this is a heavy surface that will be unwieldy for an agent to navigate and select from. Each tool does represent a distinct data product, but the sheer volume exceeds what earns its place in a coherent MCP tool set. A door-based catalog design might work better with a smaller number of parameterized tools.

Completeness4/5

The core workflow is well covered: per-door search, cross-door search, single-document retrieval via ?id=, paginated page retrieval, and payment handling are all present. Minor gaps exist, such as no tool to enumerate all available doors/catalogs or inspect schemas, and firm-check returns only citations rather than bodies. Overall it's a complete access lifecycle for the data-shop domain.

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