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

Annotations already establish readOnly and idempotent behavior, but the description adds substantial context beyond them: exact status semantics (pending while queued, liked once sent, failed/cancelled with reason) and the like_not_found response for untracked likes. This is precisely the behavioral detail an agent needs to interpret results.

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 core read operation, then the follow-up guidance and the key exclusion. Every sentence adds useful information with no repetition or filler.

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?

An output schema exists, so return values need not be re-explained. Combined with the status semantics, error case, and clear pointer back to like_post, the description is complete for an agent to invoke and interpret this tool correctly.

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 single post_urn parameter is already fully documented in the schema, including the warning that a post URL will be refused. The description does not add parameter syntax or format details beyond what the schema provides, so the baseline of 3 is appropriate.

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?

The description states a specific verb and resource — 'Read back the latest like this account queued for a post or a comment' — and immediately enumerates the possible statuses (pending, liked, failed, cancelled). It is easy to distinguish from like_post because it explicitly frames itself as a follow-up read.

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?

It gives an explicit when-to-use: 'Use it to follow up on a like_post.' It also defines an important when-not / edge case: likes created via the Taplio app's own like button are not tracked and return like_not_found. That removes ambiguity about what this tool covers.

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