dca-tools

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.

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

No annotations are provided, and the description does not disclose behavioral traits such as read-only nature, rate limits, or side effects. It is a simple read operation, but the description lacks explicit transparency beyond the immediate action.

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 with no wasted words. The first sentence front-loads the purpose and returned fields. Highly efficient.

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?

Without an output schema, the description adequately lists what is returned (category, calculator URL, historical data flag). However, it does not mention pagination, ordering, or potential limits, making it slightly incomplete for a thorough 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% with one optional enum parameter. The description adds context by naming the filter options, but the schema already enumerates 'crypto', 'stocks', 'commodities', so the added value is marginal.

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 the tool returns every asset with specific fields (category, calculator URL, historical data availability). It distinguishes from siblings like 'get_method' and 'run_dca_backtest' which serve different purposes.

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?

The description mentions an optional category filter and implies usage for listing assets, but does not explicitly state when to use this tool versus alternatives or provide exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations provided, so the description must disclose behavior. It mentions date clamping and lists return values, but does not state whether the operation is read-only (simulation is non-destructive) or any required permissions. While it covers core behavior, it lacks some safety context.

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 front-load the purpose and return values, with no redundant information. Every sentence adds value, and the structure is efficient.

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?

Given 5 parameters (3 required), no output schema, and no annotations, the description covers the essential purpose, return values, and date clamping edge case. It is nearly complete for a simulation tool, missing only error handling or validation details.

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%, so the baseline is 3. The description does not add additional parameter-level details beyond what the schema already provides. It lists return values but no parameter meaning enrichment.

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 simulates dollar-cost averaging using a specific engine and historical data. It distinguishes itself from siblings like get_method and list_assets, which are about retrieving method info and asset lists, not simulation.

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?

The description explains what the tool does and returns, and mentions date clamping. However, it does not explicitly state when to use vs. alternatives or provide exclusions. Siblings are sufficiently different to imply usage, leaving minimal ambiguity.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.