audit_csv

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

There are no annotations, so the description carries the full burden. It discloses what data is checked and that it excludes promo cards, but it does not describe the output format, whether it modifies the CSV, or any API-related behavior (e.g., rate limits, failure modes). The description adds value but leaves several behavioral aspects implicit.

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 concise and well-structured: a one-sentence summary, a brief detail paragraph, and a compact args section. Every sentence provides useful information without redundancy or fluff.

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?

The tool has a single simple parameter and an output schema (not shown), so the description does not need to detail return values. It covers the core purpose, when to use it, and parameter semantics. It could mention that the audit involves live API calls and potential latency, but overall it is sufficiently complete for the tool's simplicity.

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 input schema only defines 'csv_path' as a required string with no description. The tool description adds meaningful semantics by specifying it must be an 'Absolute path to an enriched Lorcana collection CSV,' clarifying the exact expected input beyond the schema.

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 uses a specific verb ('Audit') and resource ('enriched Lorcana collection CSV against live API data'), clearly stating the tool's function. It also enumerates exactly which fields are checked (Ink color, cost, card type, etc.), distinguishing it from sibling tools like enrich_csv or search_cards.

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 states when the tool is useful ('after a new set releases or if enrichment data looks suspicious'), providing clear context for usage. It does not explicitly name alternative tools or exclusion scenarios, but the use cases are sufficiently specific.

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