Get Backtest Daily

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

Annotations already declare the operation as read-only, idempotent, non-destructive, and open-world. The description adds useful behavioral context by stating that auth with PROPLAB_API_KEY is required and by listing the returned data fields, which goes beyond the annotation coverage.

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?

The definition is two tight sentences with no redundancy. The core output is front-loaded, followed by auth and usage notes, so 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?

For a read-only, three-parameter tool with complete schema coverage and no output schema, the description is nearly complete: it names the returned fields and auth requirement. It still does not cover sibling alternatives or date-range defaults, but those are minor gaps given the annotations and schema.

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 description coverage is 100%, so all three parameters are already documented in the schema. The description does not add meaning, format details, or constraints 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description specifies the resource and granularity: day-by-day backtest results, including hits, misses, daily profit, and cumulative profit. It is clear and distinct in granularity from siblings like backtest_summary, but it does not explicitly name or contrast those siblings.

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 phrase 'Good for charting profit curves' gives one implied use case, but there is no explicit guidance on when to choose this over backtest_summary, backtest_by_rating, or backtest_by_stat, nor any when-not guidance.

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