analyze_logs

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool analyzes text for errors and warnings but doesn't describe what the analysis entails (e.g., pattern matching, severity levels, output format), whether it's read-only or has side effects, or any limitations (e.g., performance, supported log formats). This leaves significant gaps in understanding the tool's behavior.

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 a single, efficient sentence that front-loads the core purpose ('Analyze text for errors and warnings in logs') and includes helpful examples in parentheses. There's no wasted verbiage, making it easy to parse and understand quickly.

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 (analyzing logs for errors/warnings), lack of annotations, and no output schema, the description is insufficient. It doesn't explain what the analysis returns, how errors/warnings are identified, or any behavioral traits. This leaves the agent with inadequate information to use the tool effectively beyond basic invocation.

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 schema description coverage is 100%, with the single parameter 'text' well-documented in the schema. The description adds minimal value beyond the schema by implying the text should contain logs, but doesn't provide additional semantics like format requirements or examples. This meets the baseline for high schema coverage.

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's purpose: 'Analyze text for errors and warnings in logs' with specific examples of log types (compilation, npm, Docker, runtime). It uses a specific verb ('analyze') and resource ('text for errors and warnings in logs'), but doesn't explicitly distinguish from sibling tools like 'analyze_language' or 'validate_data', which might have overlapping domains.

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 no guidance on when to use this tool versus alternatives. It mentions log types but doesn't specify use cases, prerequisites, or exclusions. With sibling tools like 'analyze_language' and 'validate_data' present, there's no indication of how this tool differs or when it's the appropriate choice.

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