Instagram account insights + audience demographics

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

Beyond the readOnlyHint and destructiveHint annotations, the description discloses crucial behavioral traits: the deprecation of 'impressions' and the refusal of unknown metrics, the threshold under which demographics are not returned (100 followers/engagements), and the meaning of an absent block (never an empty audience). It also states prerequisites and credit cost.

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?

Although lengthy, the description is front-loaded with the core purpose and alternates, then systematically covers caveats. No sentence is wasted; every clause serves a distinct function. The strong typographic emphasis for deprecation and threshold details aids scannability.

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 tool's complexity (7 params, no output schema), the description is remarkably complete: purpose, alternatives, metric details, deprecation warnings, threshold behavior, prerequisites, and read-only nature. An agent has enough to call it correctly without missing critical caveats.

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%, so baseline is 3. The description adds semantic value by explaining that demographic metrics require a breakdown and that timeframe applies only to demographic metrics, and clarifies the relationship between metrics and breakdown. This goes beyond the schema's terse descriptions.

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 an explicit verb ('ACCOUNT-level performance') and resource ('Instagram Business account'), enumerates the metrics returned, and explicitly distinguishes from sibling tools ('Use meta_post_insights for one post and meta_page_insights for the Facebook Page'). An agent can immediately understand scope and uniqueness.

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 provides direct guidance on when to use this tool versus alternatives by naming meta_post_insights and meta_page_insights, and clarifies that it covers account-level data. It also explains that demographic metrics are the 'who' read, giving contextual usage.

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