aggregate-logs

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

No annotations are provided. The description states it computes statistics and lists supported aggregation types, but does not disclose read-only nature, permission requirements, rate limits, or behavioral traits beyond basic functionality. With no annotative support, this is insufficient for a full behavioral understanding.

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 with 4 sentences, front-loaded with purpose, examples, supported aggregations, and an alternative tool reference. No redundant information, though the example list could be more structured. It is efficient for its length.

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 (nested parameters, no output schema, many features), the description only covers basic usage and aggregation types. It omits details on grouping, sorting, filtering, time ranges, and return format. The agent would lack sufficient context to use advanced features 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?

Schema description coverage is 0% for 4 complex nested parameters. The description adds no explanation of filter, compute, groupBy, or options fields. The list of aggregation types hints at possible values but does not map to schema structure. The agent cannot infer parameter semantics from the description.

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 the tool computes statistics and aggregations on logs, provides concrete examples ('how many errors per service'), and distinguishes from sibling tool search-logs by specifying the alternative for raw content.

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 suggests when to use the tool (aggregation queries) and provides an alternative (search-logs for actual content). However, it does not compare with other aggregate-* tools for different data types, but the focus on logs makes usage clear.

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