get_log_errors

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

No annotations are provided, so the description bears full responsibility. It discloses that 'Raw log messages are never returned,' which is a key behavioral trait. However, it does not mention other aspects like authentication, rate limits, or potential side effects, leaving some gaps.

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 three sentences, each serving a distinct purpose: stating what it returns, what it does not return, and when to call it. No extraneous information.

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 simple input schema (one optional parameter) and no output schema, the description covers the return value (pattern summaries, counts, frequencies), non-behavior (no raw logs), and use cases. It is complete for the tool's complexity.

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 100% with one optional parameter. The description adds value by specifying that the logGroup filter accepts a 'name substring,' which is more precise than the schema's 'name (optional).' This helps the agent understand how to use the parameter.

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 'Returns recent error pattern summaries from CloudWatch log groups: pattern counts and frequencies grouped by log group.' This is a specific verb and resource, and it distinguishes this tool from sibling tools like get_lambda_overview or get_s3_overview which focus on different AWS resources.

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 says 'Call this when investigating errors or identifying log groups with no retention policy.' This provides clear context for usage. It does not mention alternatives or when not to use, but the use case is well-defined.

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