Get Logs

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

The description goes beyond annotations (readOnlyHint, idempotentHint) by detailing pagination, ordering behavior, default values, and source-specific behaviors (e.g., 'order' applies to time-ordered sources, ignored for 'logger'). It also explains that 'compact' strips attribute dicts and that 'slug' disambiguation is handled by the 'source' param. No contradictions with annotations.

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 well-structured with sections and bullet points, making the dense information scannable. However, it is somewhat lengthy (8 paragraphs) and could be trimmed slightly without losing clarity. Every sentence adds value, but the overall length might overwhelm an agent.

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 11 parameters, no required fields, and an output schema present, the description covers all aspects: source selection, parameter applicability, default values, and ordering. It leaves no ambiguity about how to construct a valid request or interpret results.

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?

With only 9% schema description coverage, the description fully compensates by explaining all 11 parameters: source, slug, level, limit, order, offset, search, compact, end_time, entity_id, hours_back. It provides context-specific semantics (e.g., 'search' matches integration domain for source='logger', 'order' sets read direction for raw-text sources).

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 it gets HA logs from six distinct sources, each with a specific purpose (e.g., 'logbook' for state change history, 'system' for structured errors). This verb-resource pairing is specific and differentiates from sibling tools like ha_get_history, which likely retrieves historical state changes rather than log sources.

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 detailed guidance on when to use each source (e.g., 'supervisor' requires a slug, 'logger' confirms level changes). It shares common parameters and notes that some params are source-specific. However, it does not explicitly mention when to avoid this tool in favor of siblings or provide negative examples.

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