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Glama

AssayChain — Mineral Intelligence (USGS and Field Runs)

china_trade_control

Read-onlyIdempotent

China export restriction check for restricted minerals (gallium, germanium, graphite, antimony, tungsten, tellurium, rare earths). Returns restricted status, effective date, and source. Full data requires $0.25 USDC via GET /api/trade-controls/{commodity} using x402 on Base.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
commodityYesMineral commodity slug.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
paymentYes
commodityYes
restrictedYes
paid_endpointYes
restriction_dateYes

TDQS

A4/5.0
Behavior4/5

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

Annotations already indicate read-only and idempotent behavior. The description adds valuable context: return fields (restricted status, effective date, source) and the payment/API details (0.25 USDC, GET endpoint, x402 on Base). No contradiction with annotations.

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

Conciseness5/5

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

Two concise sentences: the first states purpose and scope, the second provides critical payment and endpoint details. No redundant filler or unnecessary background.

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 simple one-parameter tool with output schema and annotations, this description covers the essential information: what it does, key return fields, and required payment. Slight ambiguity remains about what 'full data' means without payment and how non-restricted commodities are handled.

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?

The schema already provides full parameter coverage with an enum and description. The description lists some relevant minerals but does not add deeper semantics about how the commodity string should be formatted or what values are valid beyond the schema.

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?

Description clearly states the tool checks China export restrictions for specified minerals and lists examples. This specific verb plus resource scope distinguishes it from sibling tools like supply_resilience or criticality.crosscheck.

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?

Use case is implied (check export restriction status for a commodity), but there is no explicit guidance on when to prefer this over alternatives or when not to use it. The payment caveat is practical but not a substitute for usage direction.

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.

Resources