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Glama

Blocksize Agentic Market Intelligence

Live Data Endpoint Builder

get_market_data_endpoint
Read-onlyIdempotent

Build the exact x402-protected HTTP URL for one live market-data request. Returns method, URL, service notes, pricing docs, and next steps; it is read-only and does not fetch prices, charge a wallet, or submit payment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesExact pair or ticker to use in the paid HTTP URL, such as BTC-USD, AAPL, MSFT, NVDA, EURUSD, or XAUUSD. Use search_pairs first if unsure.
serviceYesLive HTTP data service to prepare: vwap for crypto VWAP, bidask for crypto pairs or catalog-confirmed equity symbols such as AAPLXUSD, state for AMM state price, vwap30m for latest completed 30-minute close, vwap24h for fixed 24-hour VWAP from the stream cache, fx for currency pairs, or metal for metals.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already provide readOnlyHint and idempotentHint, so the bar is lower. The description adds value beyond annotations by stating it does not fetch prices, charge a wallet, or submit payment, and by outlining the response structure (method, URL, service notes, etc.). 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?

A single, information-dense sentence that front-loads the core action and includes return items and constraints. No filler; every clause 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?

The description explains the return contents and safety profile, and the output schema exists. It could add an explicit pointer to when to use this versus fetch or get_pricing_info, but the core purpose and limitations are covered sufficiently for an agent to use it correctly.

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 schema already documents both parameters thoroughly. The tool description does not add any parameter-level meaning beyond what the schema provides, so the baseline of 3 applies.

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 states a specific verb ('Build') and a specific resource ('exact x402-protected HTTP URL for one live market-data request'), and distinguishes itself from data-fetching tools by explicitly noting it does not fetch prices or charge a wallet. It also lists its return contents, making it unmistakable from siblings like fetch or get_pricing_info.

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 implies when to use this tool (when you need to construct a URL for a paid request) by clarifying it does not execute the request, but it does not explicitly name alternatives or say 'use X instead'. The purpose is clear enough that an agent can infer the distinction, but explicit routing to a sibling would earn a 5.

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.

Resources