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gold-silver-analytics

Filter & rank the coverage universe

get_screen_data
Read-only

Structured screen over the free-subset feed: optionally filter by metal (Au/Ag), jurisdiction (country), and stage (DEVELOPER/PRODUCER/HYBRID/EXPLORER/RESOURCE_ACQ), optionally sort by 2028 RR Score descending, and cap with limit. An analytical ranked classification — never a 'best stock' list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax rows to return.
metalNoPrimary metal: Au/gold or Ag/silver.
stageNoStage/type_code substring, e.g. DEVELOPER, PRODUCER, HYBRID.
sortByRrNoSort by rr_score_2028 descending when true.
jurisdictionNoOperating country of the primary asset, matched exactly (case-insensitive), e.g. 'Canada', 'Mexico', 'Australia'. Countries only — a state or province such as 'Nevada' matches nothing; use 'USA'.

TDQS

A4.2/5.0
Behavior4/5

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

The readOnlyHint and openWorldHint annotations are complemented by the description's disclosure that this operates on a 'free-subset feed' (a limitation) and that output is an 'analytical ranked classification' not a recommendation. This adds behavioral context beyond the annotations, though it doesn't detail rate limits or pagination. 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?

The description is highly concise: two sentences, front-loaded with the core functionality and ending with a caveat. Every phrase adds value, from the free-subset scope to the filter/sort options. There is no redundant wording or filler.

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?

Despite no output schema, the description covers the tool's purpose, filters, sorting, limit, and a key caveat. It doesn't describe the exact output fields, but given the interactive nature and sibling context, this is reasonably complete. The free-subset limitation and analytical classification add important context. A fully complete description might mention whether results include score values or just tickers, but it's not a critical omission.

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 description coverage is 100%, so parameters are fully documented in the schema. The description restates a few parameter values (e.g., Au/Ag, country, stage values) but doesn't add meaning beyond the schema except clarifying that jurisdiction means a country (though the schema already states that). It adds no syntax or format details, so a baseline 3 is appropriate.

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 the tool performs a structured screen over the free-subset feed, with specific filters (metal, jurisdiction, stage) and optional sorting and limit. This distinguishes it from siblings like get_rr_score (single score) and search_tickers (search) by emphasizing a ranked analytical classification. The verb 'screen' plus resource 'coverage universe' is specific and unambiguous.

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?

The description provides clear context: it's for filtered/ranked screening over a limited feed, and explicitly notes 'never a best stock list' to exclude financial advice usage. It doesn't name alternatives explicitly, but the context of filters and the analytical caveat gives a good sense of when to use it. A minor gap is not mentioning when to prefer search_tickers or list_tickers.

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

A4.4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: get_rr_score provides detailed analysis for a specific ticker, get_screen_data offers filterable/rankable cross-sectional data, list_tickers simply enumerates all symbols, and search_tickers performs fuzzy lookup. There is no functional overlap between these operations.

Naming Consistency5/5

All four tools follow a consistent verb_noun snake_case pattern: get_, get_, list_, search_. The naming is uniform and predictable, making it easy for an agent to infer the action and resource for each tool.

Tool Count5/5

Four tools is well-scoped for a specialized analytics server. The set covers the essential operations—single-asset deep dive, screening, directory listing, and search—without unnecessary bloat or missing core functionality.

Completeness5/5

The tool surface is complete for the stated domain of free-subset precious-metals analytics. Users can discover the universe (list_tickers), locate specific companies (search_tickers), get detailed 9-factor scores (get_rr_score), and perform structured screening (get_screen_data). No obvious gaps or dead ends are apparent.

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