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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the description earns credit for the behavioral context it adds: lexical-only matching with no embeddings, and that results are untrusted transcripts where assistant text is unverified and current facts take precedence. It also discloses provenance (conversation id, dates, source path), which is exactly the kind of context an agent needs before trusting output.

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?

Four tight sentences, front-loaded with scope and the key negative constraint, then matching semantics, then trust caveat and the escalation alternative. No filler; every clause constrains agent behavior.

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?

With no output schema, the description compensates by describing what results contain (citations to conversation id, dates, source path). Combined with the scope and trust caveats, an agent has everything needed to call and interpret this 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 100% and both parameters (query, limit) are documented with bounds and defaults. The description only adds the lexical-matching nature of 'query' ('exact words'), which is marginal beyond the schema. Baseline 3 applies when the schema carries the load.

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?

States a specific verb+resource beyond the bare name: it searches only imported ChatGPT conversation notes, not live conversations. The explicit contrast with retrieve_memory, search_memory and search_text makes it distinguishable from siblings without opening any schema.

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?

Gives clear positive scope (imported notes) and a negative condition (never reads live conversations), plus the explicit alternative 'use retrieve_memory for them'. It doesn't differentiate against sibling lexical tools like search_text/search_memory, which is why it stops short of a 5.

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