get_media_posts

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'recent media posts' and 'engagement metrics,' but doesn't specify what 'recent' means (time window), what types of posts are included (e.g., images, videos, reels), or the format of engagement metrics (e.g., likes, comments, shares). It also omits critical details like rate limits, authentication requirements, or pagination behavior beyond the 'after' parameter in the schema.

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?

The description is a single, efficient sentence that front-loads the core purpose. Every word earns its place: 'Get' (action), 'recent media posts' (resource), 'from Instagram account' (context), 'with engagement metrics' (key feature). There's no redundancy or fluff.

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?

Given the complexity of retrieving social media data with no annotations and no output schema, the description is incomplete. It lacks details on authentication needs, rate limits, error conditions, the structure of returned posts, or what 'engagement metrics' include. For a tool that likely interacts with an external API and returns rich data, this minimal description leaves significant gaps for an agent to operate effectively.

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?

The input schema has 100% description coverage, providing clear documentation for all three parameters. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't clarify if 'account_id' defaults to the authenticated user's account). With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 clearly states the tool's purpose: 'Get recent media posts from Instagram account with engagement metrics.' It specifies the verb ('Get'), resource ('media posts'), and includes the valuable detail about engagement metrics. However, it doesn't explicitly differentiate from sibling tools like 'get_hashtag_media' or 'get_stories' that also retrieve media content.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an authenticated business account), nor does it compare to sibling tools like 'business_discovery' or 'get_hashtag_media' that might retrieve similar data. The agent must infer usage from the tool name and schema alone.

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