get_altitude_lpf

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

With no annotations, the description carries the burden. It correctly implies a read operation ('Get') and adds meaning about the value's effect. No mention of side effects or return structure, but adequate for a simple getter.

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 concise sentences with no fluff. Front-loads the purpose and immediately provides the key parameter info in a structured format.

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?

Adequately explains the parameter meaning and effect, but lacks usage context within the broader tuning workflow. No mention of the corresponding setter tool, though it is present in siblings.

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?

No parameters in schema, so description adds all meaning. It explains the value type (UINT16), range (10–5000), default (300), and unit (Hz×10), which is highly informative.

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?

Clearly states the tool gets the low-pass filter cutoff for altitude estimate, explains the trade-off between smoothness and lag, and distinguishes from other altitude-related getters like get_altitude and get_altitude_d_lpf.

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?

No explicit guidance on when to use this tool versus alternatives. The context implies it's for reading a tuning parameter, but lacks direct advice for selection.

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