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 key behaviors: it retrieves patterns with confidence >= 5, results are sorted by confidence descending, and it explains the difference between compact and full return modes. It doesn't mention rate limits, authentication needs, or error conditions, but provides substantial operational context.

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: purpose, usage guidelines, parameter explanations, and return format. Every sentence adds value, though it could be slightly more concise in the parameter explanations. The information is front-loaded with the core purpose and usage guidance appearing first.

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 (pattern retrieval with filtering and output modes), no annotations, and the presence of an output schema, the description provides excellent completeness. It covers purpose, usage context, parameter semantics, and return behavior. The output schema handles return value documentation, so the description appropriately focuses on operational guidance.

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 semantic explanations for all 4 parameters. Each parameter gets clear documentation: 'project' explains current vs. specific project behavior, 'category' lists valid values, 'keyword' describes substring matching behavior, and 'compact' explains the significant difference in output size and use cases.

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: 'Retrieve mature patterns (confidence >= 5) to guide your current behavior.' It specifies the verb ('retrieve'), resource ('mature patterns'), and qualification ('confidence >= 5'). It distinguishes from sibling tool 'list_instincts' by emphasizing 'only validated patterns (not every observation).'

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 provides explicit guidance on when to use this tool: 'Call this at the start of a task to learn how similar work has been handled before.' It also gives clear alternatives: 'Prefer this over list_instincts when you want only validated patterns' and 'Use list_instincts to see seedlings too.' This covers both when-to-use and when-not-to-use scenarios.

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