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

With no annotations, the description fully discloses behavior: auto-detection of source, aggregation per account, materiality thresholds (≥5% relative AND ≥$100 absolute), severity levels (high, medium, low), max limits (5,000 rows, 5 MB per period), and error conditions. It also describes the output (flag list, roll-up, shareable URL).

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 description is comprehensive but slightly long. It front-loads the core purpose and then details. Each sentence is informative, but some redundancy exists (e.g., repeating threshold details). Overall, it is well-structured and earns its length, but could be marginally tighter.

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 the complexity (two CSV inputs, auto-detection, threshold logic) and no output schema, the description covers inputs, limits, error conditions, and output ('flag list ordered by largest delta, a roll-up, and a shareable URL'). It also mentions severity levels. An agent has enough context to invoke or avoid this tool.

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 descriptions for each parameter. The tool description adds context beyond schema: it clarifies that periodACsv is earlier period, periodBCsv later, and explains optional labels for human readability. It also ties parameters to the overall logic (e.g., source auto-detection). This adds meaningful value.

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 compares two periods of journal-entry data and flags accounts with material variance. It specifies auto-detection of source (QBO or Xero) and defines thresholds. It distinguishes from sibling tools like analyze_balance_sheet or analyze_profit_loss by focusing on journal variance.

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 explicitly tells when to use: 'when a user pastes two periods and asks "what changed?", "show me variances", etc.' It also sets constraints: both periods must be same source, mixing returns error, and provides max rows/sizes. No alternative tools are named, but the context is clear.

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