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Bnm My

by io.github.pipeworx-io

Bnm Exchange Rates

bnm_exchange_rates
Read-onlyIdempotent

Foreign exchange rates against the Malaysian Ringgit (MYR) from Bank Negara Malaysia. Latest rates for all currencies (default), one currency, or one currency on a specific historical date. Rates are published per session (snapshot time) and quote basis. Returns buying/selling/middle rates per currency unit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoHistorical date YYYY-MM-DD, e.g. "2026-05-28". Only valid together with a "currency". Omit for latest.
quoteNoQuote basis: "rm" (units of MYR per 1 foreign) or "fx" (units of foreign per 1 MYR).
sessionNoRate snapshot session time (24h). Defaults to BNM default if omitted.
currencyNoISO currency code, e.g. "USD", "SGD", "EUR". Omit to get all currencies. Required if "date" is given.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations indicate read-only, idempotent, and non-destructive behavior. The description adds that rates are per session and quote basis, returns buying/selling/middle rates, and clarifies default behavior (all currencies) and constraints (date requires currency). No contradictions.

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, front-loaded with main purpose and immediate details. Every sentence adds value with no waste.

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?

Covers all key aspects: source, currency options, date, session, quote basis, output types. With annotations providing safety profile and no output schema, it is sufficiently complete for an agent to use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with detailed parameter descriptions. The description adds context about session snapshots, quote basis, and output rates, providing meaning 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?

The description clearly states the tool retrieves foreign exchange rates against MYR from Bank Negara Malaysia. It specifies options for latest rates, one currency, or historical date, distinguishing it from sibling tools like bnm_base_rate or bnm_gold_kijang_emas.

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 on when to use (latest rates, by currency, historical date) with examples. It does not explicitly state when not to use or compare to alternatives, but it is adequate for an AI agent to select correctly.

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

A3.8/5.0
Disambiguation2/5

Many tools occupy clearly different niches, but ask_pipeworx and ask_pipeworx_beta are currently identical, ask_pipeworx_grounded and deep_research heavily overlap the same router concept, and bet_research/polymarket_edges/polymarket_arbitrage all target similar 'find an edge' territory. An agent would need to read very long descriptions carefully to avoid selecting the wrong tool.

Naming Consistency4/5

Names are consistently lowercase snake_case and usefully grouped by prefixes like bnm_, polymarket_, and pipeworx_, which makes the set fairly scannable. However, conventions mix verb-first names (ask_, discover_, resolve_, validate_) with noun-phrase names (entity_profile, recent_alerts, recent_changes), so it is not a uniform verb_noun pattern.

Tool Count2/5

36 tools is well beyond the typical well-scoped 3-15 tool range, and the server bundles several distinct domains: BNM data, the Pipeworx research platform, prediction-market analysis, and memory/subscription management. This breadth would be better split into separate focused servers.

Completeness4/5

The BNM-specific surface is well covered, with dedicated tools for the main series plus a generic bnm_endpoint passthrough for anything else. The broader data side is also unusually complete, with routing, grounded answers, deep research, entity resolution, profiles, comparisons, and claim verification; only minor gaps remain, such as no dedicated historical endpoint for some BNM series.

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