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

Annotations already mark this as read-only, and the description adds useful behavioral nuance by noting the AI analysis is only included 'when available' and enumerating its components. This helps set expectations without contradicting the annotations.

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?

A single well-structured sentence that front-loads the primary action and detail, then adds the source-of-id guidance. No wasted words; every part 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 simple read-only single-parameter tool, the description covers what the result contains, the conditional analysis, and how to obtain the id. It does not detail the full return structure, but with no output schema and a straightforward resource, the provided context is sufficient.

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 post_id described as 'Post id (UUID) or Instagram shortcode'. The description adds that the id should come from list_viral_posts or list_analyzed_posts, reinforcing usage but not adding materially new parameter semantics.

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 uses a specific verb ('Get') and resource ('full detail of one viral post'), and it states the unique value-add: the AI analysis with hook, structure, why it went viral, and replication guide. This clearly distinguishes it from the sibling list tools and preview tools.

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?

The description explicitly tells the agent to pass the post id returned by list_viral_posts or list_analyzed_posts, which provides clear context for when this tool is appropriate. It does not mention when not to use it or name alternatives, but the provenance guidance is strong.

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