save_baseline

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

The description states 'stores as a session variable', which is a stateful write, while annotations declare readOnlyHint=true. This is a direct contradiction about the tool's side effects. The computation details are useful, but the contradiction dominates and confuses the behavioral profile.

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 a single, tightly packed sentence that front-loads the action ('Save a metric baseline') and supplies the key behavioral details without extra filler. Every clause earns its place, and no redundant phrasing appears.

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?

The description covers the computation, storage mechanism, and intended later use, which is good for a tool with no output schema. However, it does not state what the tool returns or confirms after storing, and the annotation contradiction about read-only behavior undermines the agent's ability to fully understand the operation's side effects.

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 the input schema already documents all parameters. The description adds the conceptual context of computing statistics over historical data, but it does not explain parameter-specific semantics beyond what the schema already provides. This matches the baseline for high schema coverage.

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 a specific action ('Save a metric baseline'), the data source ('historical data'), the computation performed (mean, min, max, stddev), and the outcome ('stores as a session variable'). This makes the tool's function clear. However, it does not explicitly name or contrast a sibling tool like compare_to_baseline, so it stops short of full differentiation.

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 by saying the baseline is stored 'for later comparison', which hints at a workflow involving compare_to_baseline. It does not explicitly state when to use this tool versus alternatives, nor does it provide any exclusions or prerequisites, so guidance is implied rather than explicit.

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