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start_drill

Begin a standalone case question drill, with optional targeting of weak areas to improve interview performance.

Instructions

Begin a drill: loose questions pulled across cases, no full-case context.

This is the "only hard math" mode. Each question carries its own standalone framing so it makes sense out of case order. With target_weaknesses, the sampler leans toward what they keep getting wrong without excluding the rest.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoSkill tags, e.g. breakeven, market_sizing
countNo
speedNomoderate
typesNoQuestion types to drill, any of ['structure', 'math', 'exhibit', 'brainstorm', 'synthesis']. Omit for all.
max_difficultyNo
min_difficultyNo
target_weaknessesNoBias selection toward areas the candidate has scored badly on.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the burden of behavioral disclosure. It explains the sampling behavior with 'target_weaknesses' and notes that each question is standalone. However, it omits potential side effects (e.g., whether it resets progress) and includes a puzzling 'only hard math' phrase that could mislead.

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?

The description is concise and front-loaded, using two sentences to convey the core purpose and a key behavioral nuance. Every sentence earns its place with no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description gives an overview of the drill mode and sampling behavior, but the 'only hard math' phrase contradicts the available 'types' parameter (which supports non-math types). With 7 parameters and low schema coverage, the description does not fully equip an agent to correctly invoke the tool.

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

Parameters3/5

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

Schema coverage is only 43%, so the description should compensate. It adds valuable detail for 'target_weaknesses' (bias without excluding the rest), but leaves tags, count, speed, and difficulty parameters unexplained, leaving a gap for those.

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 that 'start_drill' begins a drill mode with loose questions pulled across cases and no full-case context. It differentiates from sibling tools like 'start_case' by specifying the standalone nature of the drill.

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 gives a clear context for when to use this tool: when you want a drill of standalone questions without case context. It implies a distinction from full-case tools but does not explicitly name alternatives or exclusions, so it falls short of a 5.

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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