Conversations: Conversations Filter

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

Annotations only cover the safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true). The description adds genuinely useful non-schema behavior: dual auth paths (User API key or Agent bot key via api-access-token header), the concrete endpoint, extra_body merge semantics, and that Persian/Arabic-Indic digits are forwarded unchanged. It does not explain pagination limits or result shape.

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?

Purpose is front-loaded in the first clause, with auth and body notes following in a compact block. Mild redundancy in 'Body fields: payload' since payload is fully specified in the schema, but no genuinely wasted sentences.

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?

No output schema exists, but the description covers the operation, auth, endpoint and body-extension mechanism, which is most of what an agent needs. Gaps are minor: no note on pagination behavior/limits and no mention of the non-read-only annotation despite the filter semantics, though the schema example adequately carries the filter DSL.

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 100%, so the baseline is 3 and the schema already documents payload, page, account_id and extra_body with an example. The description goes slightly beyond the schema by flagging that text values pass through unchanged and that IDs/numbers may arrive in Persian or Arabic-Indic digits — a real encoding caveat not captured elsewhere.

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 ('Filter conversations') plus scoping qualifiers (custom filter options, pagination). It implicitly distinguishes itself from gapify_list_conversations by emphasizing custom filters, but never names the sibling or states the difference explicitly.

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?

Usage is only implied: an agent can infer this is the tool for filtered/advanced conversation queries versus a plain list. There is no explicit when-to-use, when-not-to-use, or alternative routing among the several nearby conversation siblings (list_conversations, get_conversation_counts).

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