top_passes

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

No annotations exist, so description must carry the burden. It warns of being 'best-effort' and 'unreliable' but does not disclose specific failure modes, error handling, or side effects.

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?

Two concise sentences, with the critical legacy warning front-loaded. No wasted words; 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?

No output schema exists, yet description fails to explain return format or behavior on failure. Given 4 parameters and no nested objects, deeper context on usage and outcomes is missing.

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 should detail parameters. It only mentions 'criterion' and 'top N' implicitly; no explanation of n, opt_path, criterion values, descending behavior, or defaults.

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 parses binary .opt files, sorts by criterion, and returns top N. It explicitly names the preferred alternative (read_optimization_csv), distinguishing from siblings.

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 states it is legacy, unreliable, and advises using read_optimization_csv instead. This provides strong when-to-use and when-not-to-use guidance.

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