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

With no annotations, the description carries the full burden. It discloses a notable behavior: returning 'insufficient_data' below the statistical floor, and it notes that insights come 'with sample sizes'. It reasonably implies a read-only analytics operation, though it does not detail response format.

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 tight sentences: first identifies the tool's outputs, second gives direct usage guidance, third reveals an important edge-case behavior. Every sentence earns its place and the front-loaded verb makes the purpose immediately clear.

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 tool with one optional parameter and no output schema, the description covers the key outputs, intended questions, and an important statistical caveat. The main gap is that the 'weeks' parameter's effect is left completely unspecified.

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 0%, and the description never mentions the only parameter, 'weeks'. The schema's min/max defines the range, but the description adds no meaning about what weeks controls (e.g., lookback window or period granularity).

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 ('this account's content performance insights') and then enumerates the exact dimensions analyzed: formats, days of week, content pillars, and top/bottom posts. This level of specificity distinguishes it from broader analytics siblings like get_analytics_overview.

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 explicitly states when to use the tool: for 'what's working', 'when should I post', and 'what content performs best'. However, it does not mention when not to use it or name alternative tools for overlapping analytics needs.

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