data_get_equity

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

With no annotations provided, the description carries the full burden and does disclose that the operation is read-only with no side effects, plus a real precondition ('Strategy Tester must be active on chart'). It stops short of describing data volume, pagination, time granularity, or failure behavior when the tester is inactive.

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?

Three labeled, front-loaded sentences covering action, trigger, side effects, and limitation with zero filler. An agent can parse the key facts in a single pass.

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, parameterless extractor with no output schema, the description covers purpose, trigger, safety, and preconditions adequately. It leaves the return shape (what a 'data point' contains, sampling cadence, size limits) unstated, which is the main residual gap.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the documented precondition (active Strategy Tester) is the only input-like constraint and it is stated. Baseline 4 applies for a parameterless tool.

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?

States a specific verb ('Extract') and a specific resource ('equity curve data points') plus the source system ('Strategy Tester'). This cleanly separates it from siblings like data_get_trades, data_get_strategy_results, and data_get_ohlcv, which return different artifacts.

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?

An explicit 'WHEN TO USE' block names concrete scenarios: analyzing drawdowns, run-ups, or plotting performance trajectory. It gives positive selection criteria but never states when not to use it or which sibling (e.g. data_get_strategy_results) to prefer instead.

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