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

Annotations cover the safety profile (readOnlyHint, openWorldHint), and the description adds valuable context beyond them: results are a sample rather than a complete liker list, a total like count is returned, and the call costs 3 credits. This sampling/partial-result caveat is exactly the kind of behavioral detail an agent needs.

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 short sentences, front-loaded with the core action, followed by return-shape and cost. Every sentence carries information; nothing is redundant.

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?

With no output schema, the description steps in to say the return is a sample of accounts plus a total like count, and flags the credit cost. This is nearly complete for a simple read tool; only pagination/sample-size limits are unaddressed.

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% and both parameters (url, shortcode) are documented in the schema, including the either/or relationship. The description adds nothing about parameter format or defaults, so the 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?

States a specific verb+resource ('Get accounts that liked an Instagram post'), clearly matching the title. It is distinguishable from siblings like instagram_comments or instagram_post, though it does not explicitly name an alternative to disambiguate further.

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 never states when to use this tool versus siblings (e.g., instagram_comments for commenters, instagram_post for post data). No prerequisites or exclusions are given, leaving usage entirely to inference from the name.

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