log_stats

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It explains the outputs but lacks details on side effects (e.g., file modification), performance implications, required permissions, or whether it is read-only. For a tool that processes a file, more transparency is needed.

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 two sentences long, with the first sentence front-loading the core purpose and outputs, and the second adding usage context. Every sentence is necessary and no repetition.

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 an output schema but the description does not mention return format; it lists outputs informally. It lacks details on file format expectations, size constraints, or behavior for missing files. Given the sibling context and parameter count, it is minimally adequate but has gaps.

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 description coverage is 0%, yet the description partially compensates by linking parameters to outputs: 'volume histogram over time' implies bucket_size controls time bins, and 'top repeated message patterns' relates to top_patterns. However, it does not explain file_path or bucket_size values thoroughly.

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 explicitly states what the tool does: 'Compute log statistics: volume histogram over time, level breakdown, and top repeated message patterns.' This clearly identifies the verb (compute) and resource (log statistics), with specific outputs that distinguish it from siblings like analyze_errors or search_logs.

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 a clear usage context: 'Useful for spotting traffic spikes, error bursts, or noisy log sources.' While it does not explicitly list when not to use or alternatives, the provided scenarios guide appropriate invocation.

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