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AssayChain — Mineral Intelligence (USGS and Field Runs)

benchmark.commodity

Read-onlyIdempotent

Discovery preview for USGS Mineral Commodity Summaries benchmark data — 20 critical minerals: copper, gold, silver, lithium, cobalt, nickel, manganese, graphite, antimony, gallium, germanium, platinum_group, rare_earths, tellurium, tin, titanium, tungsten, uranium, vanadium, zinc. Returns available field names, on-chain provenance UIDs, and the paid REST endpoint. Data is useful as one structured, EAS-attested input for supply-chain due diligence, UFLPA sourcing evidence, EU Battery Regulation 2023/1542 disclosure, and CBAM/CSDDD compliance research. Full data (grade cutoffs, spot pricing, recovery benchmarks, production statistics) requires $0.10 USDC via GET /api/benchmark/{commodity} using the x402 protocol on Base.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
commodityYesMineral commodity slug. One of: copper, gold, silver, lithium, cobalt, nickel, manganese, graphite.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYes
paymentYes
commodityYes
provenanceYes
paid_endpointYesREST endpoint for the full paid response.
schema_versionYes
available_fieldsYesTop-level field names present in the full paid response.
publication_dateYes

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds that this is a preview-only tool returning field names and metadata, and that full data requires payment via the x402 protocol. This extra context about the paid endpoint and on-chain provenance is valuable beyond annotations.

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 moderately long but structured with distinct clauses: preview nature, mineral list, return values, use cases, and payment model. It is front-loaded with 'Discovery preview' and each sentence provides meaningful information, though the compliance use-case list could be trimmed without losing core purpose.

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?

For a discovery/preview tool, the description adequately covers what it returns, the scope of commodities, and how to access full data. The output schema exists, and annotations cover safety, so the description does not need to detail return formats. It is complete enough for an agent to decide when to invoke this tool.

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?

There is one parameter with a complete enum, and the schema property description already lists valid values (though truncated). The description adds the full list of 20 critical minerals and calls them 'critical minerals', but this is largely redundant with the schema enum. With 100% schema coverage, the description does not need to add much, but it does not explain how the commodity affects the response beyond the enum.

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 states it is a 'Discovery preview' that 'returns available field names, on-chain provenance UIDs, and the paid REST endpoint.' This is specific with a clear verb and resource, and it distinguishes itself from sibling tools like 'benchmark.sample' or 'benchmark.runs' by emphasizing the discovery/preview nature.

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 use cases (supply-chain due diligence, UFLPA, EU Battery Regulation, CBAM/CSDDD) and implies when to use it: when you need a preview before paying for full data. It does not explicitly name alternative tools or provide exclusions, but the distinction between preview and paid endpoint is clear.

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

A3.6/5.0
Disambiguation4/5

Most tools target distinct data domains (operations, claims, surveys, supply, ESG, extraction). The three benchmark.* tools are clearly grouped, and supply_resilience vs supply_share are distinct in focus. Minor overlap exists between earth_mri_focus_areas and geophysics_surveys, both covering geophysical survey data.

Naming Consistency2/5

Tool names mix snake_case (active_operations, blm_claims_data) with dotted namespaces (benchmark.commodity, extract.estimate, sales.ask). There is no consistent verb_noun pattern; many are noun phrases, some are verb-led. This inconsistency makes the API surface harder to learn.

Tool Count3/5

At 19 tools, the server spans a wide domain (commodity benchmarks, extraction workflow, ESG, supply chain, surveys). While each tool has a clear role, the count exceeds the typical well-scoped range, making the surface feel heavy for an MCP server.

Completeness4/5

The tool set covers most critical mineral intelligence functions: operations, claims, surveys, benchmarks, criticality, trade, stockpile, supply, ESG, search, and extraction. Missing a direct full-data retrieval tool (payments happen via external REST endpoints) and a consolidated commodity report tool, but the coverage is strong.

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