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aaib-reports

GET https://ticks.bnm.farm/aaib-reports — $0.05 USDC on Base to 0xf59621FC406D266e18f314Ae18eF0a33b8401004. UK AAIB investigation-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

A4.4/5.0
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 it delivers: payment amount and address, HTTP 402 on unpaid requests, JSON response after a valid X-PAYMENT, chunk retrieval semantics, and the explicit note that this endpoint is not a new SKU. This is exceptional disclosure for a paid endpoint.

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 but contains no filler; every sentence conveys operational information. It could be slightly better structured for readability, but the front-loaded endpoint and payment details make it efficiently scannable.

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

Completeness5/5

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

Even without an output schema or annotations, the description tells an agent everything needed to invoke it correctly: how to select chunks, how to pay, what HTTP error to expect, and what happens after payment. The only missing piece is detailed JSON shape, which is not required here.

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

Parameters3/5

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

Schema descriptions cover all four parameters (id, page, before, x_payment) with usage details, so the description does not need to restate them. It adds pricing and HTTP behavior but not new parameter-level meaning, so the baseline 3 applies.

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

Purpose5/5

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

The description clearly specifies the resource (UK AAIB investigation-report text) and the operations available: a plain GET returns the newest chunk, ?id returns one official text, and ?before returns an older chunk. It also identifies the exact endpoint, making it easy to tell apart from report-tool siblings.

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

Usage Guidelines4/5

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

It provides concrete usage conditions: plain GET for newest chunk, ?id for the official catalog text, ?before with an id or date for older chunks, and omitting before for newest. It does not explicitly name alternative tools or exclusion cases, but the operation-specific guidance is clear enough.

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.