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Instrument Search

search_pairs
Read-onlyIdempotent

Discover supported crypto, equity, FX, and metal symbols before using the paid HTTP API. Returns up to 50 catalog matches with asset class, available services, and pricing tier; it is free, read-only, and never returns live prices or starts payment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSymbol, ticker, asset, or pair to search for, such as BTC, BTC-USD, ETH, AAPL, EURUSD, or XAUUSD.
asset_classNoOptional asset-class filter. Use all for the full catalog, crypto for digital assets, equity/equities for catalog-confirmed stock symbols such as AAPLXUSD, fx for currency pairs, or metal for metals.all

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already indicate readOnlyHint, idempotentHint, and non-destructiveness. The description adds valuable behavioral detail beyond the annotations: a 50-match limit, the kinds of data returned (asset class, services, pricing tier), and the guarantees that it is free, read-only, and does not trigger payment or provide live prices.

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 two sentences with no filler. It front-loads the main purpose, then packs the crucial constraints (free, read-only, no live prices, no payment) into a compact second sentence. Every clause adds useful information.

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?

Given the rich annotations, a fully described input schema, and an output schema, the description provides everything an agent needs to decide whether and how to call it. It covers the catalog scope, result-size cap, and safety guarantees, so no critical context is missing.

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 the input schema fully describes both the query parameter and the asset_class filter. The description does not add new parameter-level meaning beyond the schema, so it earns the baseline score for schema-documented parameters.

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 uses the specific verb 'Discover' with a clearly defined resource: supported crypto, equity, FX, and metal symbols. It also states what the tool returns (catalog matches with asset class, services, pricing tier) and distinguishes itself from live market data and payment-triggering tools by explicitly saying it never returns live prices or starts payment.

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 when-to-use context: 'before using the paid HTTP API.' It also gives exclusions by noting the tool is free, read-only, and never returns live prices or starts payment. It does not name sibling tools or explicitly contrast list_instruments/search, but the usage context is strong enough to guide selection.

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
Disambiguation4/5

Each tool has a distinct primary purpose, but search and search_pairs overlap in discovery, and get_market_data_endpoint vs get_workflow_endpoint both build endpoints. Descriptions clearly differentiate them, so confusion is unlikely.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case (get_, list_, search_, fetch). The naming is predictable and uniform across the set.

Tool Count5/5

With 8 tools covering search, catalog, pricing, and endpoint building, the count is well-scoped for a market intelligence discovery server. No redundancy or bloat.

Completeness4/5

The tools cover documentation search, instrument discovery, product/pricing info, and endpoint construction. The only minor gap is not executing actual paid data fetches, but that is intentionally left to the generated HTTP endpoints.

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