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

Annotations declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe read operation. The description adds useful behavioral context: it defines the tier boundaries (6, 15, 30) and the metrics considered (saved, read, labeled). It does not disclose edge cases like missing data or behavior with no topics, but given annotation coverage of safety, a 3 is reasonable.

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 concise, fitting in three sentences: the primary purpose, tier definitions, and example queries. All sentences earn their place, and the tier information is front-loaded. Minor redundancy with the schema's description of the optional topic parameter, but no waste.

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 only one optional parameter, no required fields, and no output schema, the description covers the input side well. It explains the output metaphor (tiers) but does not specify the exact output structure (e.g., a list of topics with counts). However, the example queries and tier definitions give a clear understanding of what will be returned. Missing performance or pagination notes, but given low complexity, it is adequate.

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 schema describes the 'topic' parameter as 'Optional: get depth for a specific topic only', which is clear. The description reinforces this by indicating the tool can be used for overall breakdown or specific topic. Since schema coverage is 100%, the description adds minimal semantic value beyond the schema; the baseline of 3 is appropriate.

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 that the tool shows engagement depth per topic, specifying metrics (posts saved, read, labeled) and auto-categories. It includes tier thresholds (Exploring, Familiar, Deep, Expert) which define the output semantics. This distinguishes it from siblings like get_stats (general stats) and get_recent (recent posts) because it focuses on topic-specific depth classification.

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 explicit example user queries ('what am I most into?', 'where am I deepest?', 'my expertise breakdown') that signal when to use this tool. However, it does not explicitly state when NOT to use it or name alternative tools (e.g., get_stats for general stats). The given examples cover the typical use case but lack exclusionary guidance.

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