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

No annotations provided, so description must disclose behavior. It mentions cost and data size, but does not describe what the tool returns (e.g., a report object) or any side effects. For a QC tool, the return structure is crucial for agent decision-making, and it is missing.

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?

Extremely concise: three lines with no superfluous content. The purpose is front-loaded, key checks are listed, and the bars format is specified. Every sentence adds value.

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 no output schema and no annotations, the description covers purpose and bars param adequately but omits the output format and the optional payment_signature parameter. For a simple tool with 2 params, this is acceptable but not fully complete.

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 0%, so description adds value. It explains the 'bars' parameter structure: expected fields (timestamp, open, high, low, close, volume) and valid size range (5..100000 rows). However, 'payment_signature' is not explained, leaving its purpose unclear.

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 performs forensic QC on OHLCV bars before backtesting. It lists specific detections (impossible bars, bad prints, etc.) and distinguishes from sibling tools like audit_backtest and trade_preflight by focusing on pre-backtest data quality.

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?

Explicitly says 'before you backtest on them', indicating when to use. Mentions cost ($0.05) as a consideration. Does not explicitly state when not to use or list alternatives, but context with siblings makes the usage clear.

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