search_addon_logs

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

With no annotations, the description carries the burden. It discloses case-insensitive filtering and token-limit avoidance. It does not explicitly state read-only nature or further behavioral traits, but the output schema mitigates need for return value details. Slight room for improvement in listing 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?

The description is highly concise: a clear purpose sentence, a note about token limits, and parameter docs. No unnecessary words, front-loaded, well-structured.

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 tool's complexity (3 params, output schema exists), the description covers purpose, usage hint, and parameter details comprehensively. No annotations, but the description compensates fully. It is complete for an agent to select and invoke correctly.

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 description adds substantial meaning to all three parameters beyond the schema: slug has an example, grep explains case-insensitive filtering, tail clarifies default behavior. Schema description coverage is 0%, so this is essential and well-done.

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 'Fetch add-on logs and filter lines by a case-insensitive substring,' providing a specific verb and resource. It distinguishes from siblings like get_addon_logs by emphasizing filtering and avoiding token limits.

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 implicitly suggests usage when logs are large to avoid token limits, but lacks explicit when-to-use or when-not-to-use guidance compared to alternatives. However, the context is clear enough for an agent to infer appropriate use.

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