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

Annotations already carry the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), lowering the bar. The description adds that the tool returns conversation content plus recent messages and characterizes them as context-bearing ('commitments and tone'). It does not disclose how many messages are returned or whether reading affects read-receipt status, so it settles at baseline.

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 sentences with zero waste. The core action and scope are front-loaded in sentence one, and the usage context follows immediately in sentence two. 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?

For a low-complexity tool (2 params, 1 required, no enums, no nested objects) with rich annotations and 100% schema coverage, the description is nearly complete: it covers the operation, the returned content at a high level, and the usage context. The only gap is that no output schema exists and 'recent messages' leaves the message-count/Time window unspecified.

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%, so the schema carries the full parameter burden: chat_id details acquisition ('Obtain with: provider list conversations/inbox chats -> chat.id'), URL visibility, and anti-patterns ('Never pass: person name, user_id, message_id'), while account_id explains multi-account disambiguation. Per the baseline rule, the description itself adds no parameter semantics beyond what the schema provides.

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 ('Read a LinkedIn private conversation') with a defined scope ('plus recent messages'). This distinguishes it from siblings like linkedin_list_conversations (which lists conversation metadata) and linkedin_send_message (which writes). An agent can tell what this tool does without opening the 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?

Provides clear usage context: 'Use before replying so the agent understands prior context, commitments and tone,' which positions it squarely in the read-context-then-respond workflow. However, it does not explicitly name alternative tools or state when not to use it, so it stops short of full when/when-not guidance.

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