sarb_cpd_ratesCurrent Corporation for Public Deposits (CPD) interest rates: interest charged and interest earned. Each item includes a TimeseriesCode usable with the sarb_timeseries tool. No arguments.
| Name | Required | Description | Default |
|---|---|---|---|
| frequency | No | Ignored; reserved. Always returns current CPD rates. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {}
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds value beyond annotations by specifying return content (interest charged/earned, TimeseriesCode). No contradictions with annotations; all hints are consistent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler, front-loads the purpose and key actionable details (TimeseriesCode). Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Coverage is good given low complexity and rich annotations. Could optionally include information about rate validity or typical usage context, but currently sufficient for selection and basic understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and already documents the single parameter as ignored. Description adds 'No arguments' which is slightly inconsistent with the presence of the parameter but clarifies usage. Does not add significant semantic depth beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly identifies the tool as returning current CPD interest rates, both charged and earned. Mentions that each item includes a TimeseriesCode for use with the sibling `sarb_timeseries` tool, effectively distinguishing it from other SARB tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
States 'No arguments' and describes relationship to `sarb_timeseries`, implying when to use that tool instead. However, lacks explicit when-not-to-use guidance or alternatives among siblings.
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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Several tools have overlapping or redundant purposes, most notably ask_pipeworx and ask_pipeworx_beta (currently identical), and the cluster of Polymarket tools (polymarket_edges, polymarket_arbitrage, bet_research) which all surface trading opportunities. While the lengthy descriptions help, an agent could easily select the wrong tool.
All tool names use snake_case with a readable verb/noun structure, and there are no casing inconsistencies. However, the verb-first vs noun-first pattern is not uniformly applied (e.g., ask_pipeworx vs sarb_timeseries vs polymarket_edge_tracker), so it's mostly consistent with minor deviations.
At 36 tools, the set is large and exceeds the 25-tool threshold; the broad scope justifies some volume but the presence of duplicate/overlapping tools (ask_pipeworx_beta, multiple Polymarket scanners) makes the count feel inflated.
The set covers a wide domain — SARB data, company research, prediction markets, AI visibility, memory, and subscriptions — with a good lifecycle for most features. Minor gaps exist (no subscription update, no bulk data export), but the core workflows are well covered.