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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and scope are covered structurally. The description adds the analytical output gist ('which format drives the most engagement'), but says nothing about row granularity, date-range behavior, or what happens for accounts with too few posts in a format — a real edge case for a breakdown tool.

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?

Two sentences, zero filler: the analytical scope is front-loaded and the usage triggers follow immediately. Nothing is repeated from the title or schema.

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 single-parameter, read-only analytics tool with no output schema, the description conveys both what is measured and what conclusion it supports. A brief note on how the breakdown is grouped (per post vs. aggregated per format) would close the last gap.

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 a single parameter that the schema itself documents as 'Instagram username (without @)'. The description contributes no additional parameter meaning, so the baseline of 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?

It names a specific verb ('Analyze') and resource ('content performance by media type') and enumerates the exact formats (Image, Video, Reel, Carousel), so the agent knows precisely what dimension is being broken down. It does not explicitly stake out its boundary against the sibling get_tiktok_content_breakdown — platform is only inferable from the schema's 'Instagram username' and the annotation title.

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 second sentence gives three concrete trigger phrasings ('which content type works best', 'what kind of posts to focus on', 'content strategy recommendation'), which is strong positive routing. It stops short of naming an alternative or an exclusion (e.g. when to prefer get_post_insights or get_reels_analytics instead).

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