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AssayChain — Mineral Intelligence (USGS and Field Runs)

supply_share

Read-onlyIdempotent

Top-3 producer supply concentration for 20 commodities. Returns country, market share %, allied/adversarial flag, Herfindahl-Hirschman Index (HHI), and total allied vs adversarial supply share. Full data requires $0.25 USDC via GET /api/supply/{commodity} using x402 on Base.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
commodityYesMineral commodity slug.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
paymentYes
commodityYes
paid_endpointYes
top_producersYes
allied_share_pctYes
adversarial_share_pctYes

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, which establishes safety. The description adds valuable behavioral context: the exact fields returned, the 'Top-3' limitation, and the paywall for full data via a specific endpoint. 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 sentences: the first front-loads purpose and outputs; the second explains access/payment. No redundant wording, no unnecessary detail. Every sentence earns its place.

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?

With an output schema present, the description need not repeat return structures. It covers the payment requirement, endpoint, and protocol (x402 on Base), which are essential for invocation. Minor gap: doesn't state data freshness, which is not critical. Complete enough for a single-parameter read 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?

The single parameter (commodity) is fully documented in the schema with an enum and description. The description merely echoes '20 commodities' without adding detail about specific values or selection behavior. With 100% schema coverage, the baseline of 3 is appropriate.

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 states the tool's function: 'Top-3 producer supply concentration for 20 commodities.' It identifies the resource (commodities) and the specific output (country, market share %, HHI, etc.). However, it does not differentiate from sibling tools like supply_resilience or china_trade_control, so it falls short of a 5.

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 implies usage through its purpose but provides no explicit 'when to use' or alternatives. The payment requirement ($0.25 USDC via x402) is an access constraint, not usage guidance. Since siblings exist but are not referenced, the usage context is only weakly implied.

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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