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

Annotations only declare it is a non-destructive, idempotent, open-world mutation; the description adds the crucial externally visible consequence that on WhatsApp this fires a read receipt (blue ticks) to the participant while on other networks it only writes local metadata.read_at, and notes the return value. That is real behavioral context beyond the structured fields.

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?

Three tight sentences, front-loaded with the action, then the platform-specific behavior, then the return value. No filler and every clause carries information.

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 single-parameter mutation with full schema coverage and annotations covering the safety profile, the description covers action, side effects, and return value. Only the absence of any precondition/routing guidance keeps it short of fully complete.

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% and chat_id already documents that it accepts a hashid or external_conversation_id, so the description adds no parameter-level meaning. 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 and resource ('Mark a chat as read') and immediately scopes the effect by platform, so an agent can tell exactly what operation this is and how it differs in behavior from any other dm_* tool.

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 implied by the operation itself, but the description never states when to prefer this over adjacent tools (e.g. dm_chat_archive) or any precondition for calling it. Adequate but leaves routing to inference.

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