list_app_conversations

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

With no annotations, the description carries the full burden; it does disclose that results are limited to conversations saved on this local machine and are partitioned by app, which is real behavioral context. It says nothing about ordering, whether limit caps the result set or how search matches, or whether the operation is read-only/paginated.

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?

Two tight sentences with the qualifier front-loaded and the substantive scope immediately after; nothing is wasted. The parenthetical disambiguating Codex variants earns its space, though 'Lead only' is left dangling as unexplained jargon.

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 three-parameter read tool with no annotations and no output schema, the description establishes what is being listed and where it lives, which is the core need. It leaves the shape of a returned conversation, pagination semantics, and the meaning of 'Lead only' unaddressed, so an agent could still invoke it without understanding the results.

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 coverage is 0%, so the description must compensate. It fully covers the only required parameter by enumerating valid app values (codex, claude-code, antigravity) that the schema does not encode as an enum, but 'limit' and 'search' receive no meaning at all.

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 concrete verb (list) and scoped resource (conversations saved on this PC, filtered by app), and enumerates the three valid app values. It stops short of distinguishing itself from read_app_conversation or list_files, which an agent could easily confuse with it.

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?

'Lead only' is a usage restriction, but it is unexplained shorthand and does not say when this tool should be chosen over read_app_conversation or get_transcript. No exclusions or prerequisites beyond that cryptic qualifier.

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