Get parameter history

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

With no annotations, the description carries the full burden. It discloses ordering (oldest to newest), limiting (most recent `limit` readings), and that it returns a time-series. However, it does not describe error cases, return format, or side effects. The provided info is adequate but not exhaustive.

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 with no wasted words. The purpose is front-loaded, followed by a practical use case. Excellent conciseness.

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 simplicity of the tool (3 parameters, no output schema, no nested objects), the description covers purpose, parameter intent, and use case. It could mention the return format (e.g., array of {timestamp, value}) to be fully complete, but overall it is sufficient for an agent to understand when and how to use it.

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 100% with each parameter described. The description adds minimal value beyond schema, only reinforcing the role of 'limit' as 'most recent readings'. Baseline 3 is appropriate as it does not significantly enhance parameter understanding.

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 'recent time-series for one PID' with ordering and limit, and gives a concrete use case ('trend charts and degradation analysis'). It effectively distinguishes from siblings like 'read_live_pids' which serves a different purpose (live data).

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 implies usage for historical trend analysis but does not explicitly state when NOT to use it (e.g., for real-time data, use read_live_pids). The context is clear but lacks explicit exclusions or alternatives.

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