Filter rlg log records

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

Annotations already state readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds behavioral context: it filters and renders records in a specified format, which is not in annotations. No contradictions.

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 exactly two sentences, front-loaded with the core action, and every sentence adds value. No unnecessary words.

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 4 parameters, no output schema, and good annotations, the description covers purpose, parameters, usage guidance, and alternatives comprehensively. It is complete for an AI 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?

Schema description coverage is 100%, so baseline is 3. The description references 'minimum severity and/or component', which maps to min_level and component parameters, but does not add significant meaning beyond what the schema already provides (e.g., format has defaults and examples in schema).

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 uses specific verbs and resources: 'Select rlg records by minimum severity and/or component and render them in any rlg LogFormat.' It clearly distinguishes itself from siblings by naming alternatives (tail_log, summarize_errors) and their purposes.

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?

Explicit guidance is provided: 'Use this to narrow a log to what matters (e.g. WARN-and-above for one service); use tail_log for a raw recent slice and summarize_errors when you only need per-component error totals.' This tells both when to use this tool and when to use alternatives.

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