memory_search

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

With no annotations provided, the description carries the full burden, and it delivers: it explains ordering of cortex vs entries, deduping behavior, contested facts routing to memory_fact_resolve, low-confidence semantics, superseded entry handling, temporal events, and even cost implications of rerank. This is unusually rich behavioral disclosure.

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 dense but well-organized: a short behavioral intro followed by a parameter list that maps cleanly to the schema. Every sentence adds information, and the most important guidance is front-loaded before the detailed argument list.

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?

For a 12-parameter tool with no annotations, this description is remarkably complete. It covers invocation context, behavioral edge cases, parameter semantics, output structure, and even default values. The rich output schema exists, but the description independently provides the behavioral context needed to call the tool correctly.

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%, but the description compensates fully by explaining every parameter's meaning and nuances: filter semantics (AND/OR), min_score's role as a relevance floor, tri-state behavior for rerank/bm25, explain implying verbose, and the default compact output shape. This exceeds what the raw schema gives the agent.

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 states a clear action ('Retrieve memories for a query') and resource ('memories'), and adds the notion of 'associative recall plus canonical facts,' which meaningfully distinguishes it from generic retrieval. However, it does not explicitly name or differentiate itself from sibling tools like memory_recall, memory_get, or memory_history, so it falls short of a 5.

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?

'Call at task start or when context may apply' is clear, actionable guidance for when to use the tool. It does not explicitly state when not to use it or name alternative tools, so it lacks the exclusions needed for a 5, but the context is well-defined.

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