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

Annotations cover safety profile (readOnlyHint=false, idempotentHint=true) but the description adds non-obvious operational context: the per-minute inbox rate cap and the anti-looping constraint. It doesn't explain whether marking read is visible to the other party, but the rate-limit disclosure is meaningful extra context.

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, front-loaded with the action then the rationale and constraint. No filler; every clause earns its place.

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?

Low complexity tool (1 required param, no output schema, no nesting). The description covers purpose, sourcing of the id, timing, and rate limits – sufficient for correct invocation. Missing only whether other participants see the read receipt.

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% with both params documented (chat_id sourced from list_inbox_chats, profile_id optional default). The description restates the chat_id basis but adds nothing beyond the schema. Baseline 3 applies.

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?

Clear specific verb+resource: 'Mark a LinkedIn conversation as read (by chat_id).' It also distinguishes the workflow stage (after AI processed a thread) and references the sibling list_inbox_chats for sourcing the id.

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?

Explicit when-to-use ('after the AI has processed/answered a thread') and explicit when-not ('do not loop this call') with a concrete rate limit (3 calls/min). This is strong routing guidance.

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