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

Annotations already declare readOnlyHint=false, destructiveHint=false, idempotentHint=true, and openWorldHint=false, so the safety profile is covered structurally. The description adds genuine value by disclosing the effect (changes surface in the Library and notices), but says nothing about what 'notices' entails, whether following a market behaves differently from following a model, or any auth requirements.

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?

One sentence, front-loaded with the action and immediately followed by the consequence. There is no filler or redundant restatement of the title.

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 one-parameter, non-destructive, idempotent write with no output schema, the description covers what the tool does and why you would want it. The remaining gaps (already-followed behavior, the distinction between following a model versus a market) are minor rather than blocking.

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 100% and the single 'id' parameter already documents that it accepts a ch: model id, a datasnack.ai/m/ URL, or a market id from search_models. The description's '(or market)' reinforces that markets are valid but adds no syntax or format detail beyond the schema, 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?

The description gives a specific verb ('Follow') and resource ('a model (or market)'), and states the observable outcome: changes appear in the reader's DataSnack Library and notices. It is distinguishable from the sibling unfollow_model by the verb alone, though it never names or contrasts that sibling explicitly.

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?

Usage is implied rather than stated: an agent can infer you call this when you want a model's changes tracked, and that unfollow_model is the inverse. There is no explicit when-to-use/when-not guidance, no mention of prerequisites (e.g., needing a model id from search_models), and no statement about what happens if the model is already followed.

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