instinct

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes what the tool returns (observations with timestamps and source projects), its purpose (tracking confidence evolution), and practical applications. However, it doesn't mention potential limitations like rate limits, authentication requirements, or data retention policies.

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 and appropriately sized. It begins with the core purpose, explains the return value and use cases, provides clear usage guidelines with alternatives, and details parameters and return structure. Every sentence adds value without redundancy, and information is front-loaded for quick comprehension.

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's complexity (historical data analysis), no annotations, and the presence of an output schema, the description provides excellent contextual completeness. It explains what the tool does, when to use it, parameter details, and the return structure, making it fully understandable without needing to examine the output schema separately.

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?

With 0% schema description coverage, the description fully compensates by providing detailed parameter semantics. It explains the 'pattern' parameter format (case-sensitive, includes prefix with example 'seq:lint->fix') and references get_instinct() for consistency. It also explains the 'days' parameter as a 'look-back window in days' with a default value of 30, adding meaning beyond what the bare schema provides.

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 with specific verb ('Show') and resource ('one pattern's confidence evolution over a time window'), distinguishing it from sibling get_instinct() which provides a snapshot rather than historical timeline. It precisely identifies what the tool does and how it differs from alternatives.

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 states when to use this tool ('for spotting growth velocity, cross-project adoption, or stale patterns that should decay') and when to use an alternative ('For a snapshot of the current state (not the timeline), use get_instinct() instead'). This provides clear guidance on tool selection based on user needs.

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