get_lab_trend

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

No annotations provided, so description must disclose behavioral traits. It only states ordering (oldest first) and that it returns a list. No mention of read-only nature, no side effects, authentication, or limitations. Minimal disclosure for a tool with no 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?

Two sentences; the first gives the core purpose, the second provides usage guidance. No redundancy, every word earns its place.

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?

While an output schema exists, the description omits any context about the marker_name parameter (e.g., expected format, possible values) and does not address potential issues like empty results or pagination. The tool's simplicity partly excuses this, but completeness is insufficient for practical use.

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 0% for the single parameter 'marker_name'. The description adds no information about what valid values are, format, or examples. The parameter is left entirely undocumented, forcing the agent to guess or rely on context.

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 returns a list of readings for a marker, ordered oldest first. The verb 'returns' and resource 'list of all readings' are specific. While siblings exist, none directly relate to lab trends, so differentiation is implicit but sufficient.

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?

Explicitly lists when to use: 'when the user asks about trends, progress, changes over time, historical readings or whether something is getting better or worse.' Provides clear context but no exclusions or alternative tools.

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