Get the DCA Method summary and key links
get_methodReturns a concise explanation of the dollar-cost-averaging method plus links to the methodology, calculators and blog.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
get_methodReturns a concise explanation of the dollar-cost-averaging method plus links to the methodology, calculators and blog.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description clearly indicates a read-only operation ('returns'), which is sufficient given no annotations. It does not contradict any annotation (none provided). The behavior is fully disclosed: it returns an explanation and links.
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?
Single sentence front-loads the main purpose ('returns a concise explanation of...') and adds secondary info ('plus links to...'). No extraneous words; every part is valuable.
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?
For a tool with no parameters, no output schema, and only two siblings, the description is complete. It tells the agent exactly what the tool provides (explanation and links) and implies it is for informational purposes.
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?
There are zero parameters, and schema description coverage is 100% (empty schema). Per guidelines, baseline is 4. The description adds no parameter info because none exist.
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?
The description clearly states it 'returns a concise explanation of the dollar-cost-averaging method plus links', specifying both the resource (DCA method) and action (returns explanation and links). It distinguishes from siblings: list_assets lists assets, run_dca_backtest runs backtests.
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?
No explicit guidance on when or when not to use this tool versus alternatives. Usage is implied by the description and sibling tool names, but there is no direct statement like 'Use this to get an overview; for backtesting use run_dca_backtest instead.'
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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Each tool has a clear, distinct purpose: explaining the method, listing assets, and running backtests. No functional overlap.
All tool names follow a consistent verb_noun pattern (get_method, list_assets, run_dca_backtest) with snake_case, making them predictable.
Three tools cover the essential needs for a DCA toolset: method description, asset discovery, and backtesting. The count is well-scoped without being too sparse or excessive.
The set covers core DCA operations, but lacks features like comparing multiple assets or customizing backtest parameters, which could be useful. Still, no critical gaps for basic usage.