suggest

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

No annotations exist, so the description carries full burden. It discloses performance (O(prefix-length)) and return structure ({name, category, path}) but does not mention safety, idempotency, or side effects. Given the tool's nature, this is sufficient.

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 sentences with no waste. First sentence states purpose and implementation, second gives examples, third states return format and performance. Front-loaded and efficient.

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 existing output schema (not shown) and no annotations, description covers purpose, behavior, performance, and return fields. Missing explanation of language parameter and explicit differentiation from search_algorithms, but overall 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 compensates partially. It explains prefix matching rules and limit cap, but does not describe the language parameter at all. Language defaults to 'python' but its effect is 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 uses specific verb 'Autocomplete' and resource 'algorithm names by prefix'. It distinguishes from siblings like search_algorithms by focusing on prefix matching and typeahead. Examples clarify the intent.

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 provides clear context for when to use (prefix-based autocomplete) and gives concrete examples. However, it does not explicitly exclude usage or mention alternatives like search_algorithms for full-text search.

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