history

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

No annotations are provided, so the description carries the full burden. It describes the return format and that it is a read-only query of observations. There is no mention of error handling, rate limits, or authentication, but for a read tool the disclosures are adequate.

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 clear sections (Args, Returns) and front-loads the purpose. Every sentence adds value without wasting words. It is appropriately sized for the tool's simplicity.

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 tool has a simple input schema, no annotations, and an output schema, the description provides all necessary context: what it does, how to use it, and what to expect. It also distinguishes from sibling tools, making it complete for agent 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 description coverage is 0%, so the description must compensate. It adds detailed semantics for both parameters: 'pattern' is explained as an exact case-sensitive key with prefix, and 'days' is described as a look-back window with default 30. This adds significant meaning beyond the schema.

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's purpose: 'Show how one pattern's confidence evolved over a time window.' It uses a specific verb and resource, and distinguishes itself from the sibling tool get_instinct (snapshot vs. timeline).

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 explicitly tells when to use this tool (for timeline/history) and when not ('For a snapshot of the current state...use get_instinct() instead'). It does not cover all possible alternatives, but provides strong context.

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